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TECHNOLOGICAL STRATEGIES OF STONE TOOL PRODUCTION
AT TABUN CAVE (ISRAEL)
by
Harold Lewis Dibble
A Dissertation Submitted to the Faculty of the
DEPARTMENT OF ANTHROPOLOGY
In Partial Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
In the Graduate College
THE UNIVERSITY OF ARIZONA
19 8 1
Copyright 1981 Harold Lewis Dibble
THE UNIVERSITY OF ARIZONA
GRADUATE COLLEGE
As members of the Final Examination Committee, we certify that we have read
the dissertation prepared by ______ Harold Lewis Dibble____________________
entitled
TECHNOLOGICAL STRATEGIES OF STONE TOOL PRODUCTION AT TABUN CAVE
(ISRAEL)
and recommend that it be accepted as fulfilling the dissertation requirement
for the Degree of ________________ Doctor of Philosophy___________________ .
Date
Vi
■'/ r . j r
-
Date
Date
Date
Date
Final approval and acceptance of this dissertation is contingent upon the
candidate's submission of the final copy of the dissertation to the Graduate
College.
I hereby certify that I have read this dissertation prepared under my
direction and recommend that it be accepted as fulfilling the dissertation
requirement.
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Director
Date
STATEMENT BY AUTHOR
This
requirements
is deposited
rowers under
dissertation has been submitted in partial fulfillment of
for an advanced degree at The University of Arizona and
in the University Library to be made available to bor­
rules of the Libraryo
Brief quotations from this dissertation are allowable without
special permission, provided that accurate acknowledgment of source
is made. Requests for permission for extended quotation from or
reproduction of this manuscript in whole or in part may be granted by
the copyright holder0
ACKNOWLEDGMENTS
Everyone who has undertaken a project for purposes of writing a
dissertation understands that it is impossible to thank all of the
people who have contributed their time, energy, and patience0
In par­
ticular I owe tremendous gratitude to Professor Arthur Jelinek for
allowing me to serve as his assistant for the past six years, and to
use the Tabun collections for research0 He has been, and will continue
to be, a valuable teacher and a close friendo
Two special thanks go to John Whittaker and Phil Chase0 John
has served as a colleague on numerous projects and will hopefully be a
lifelong knapping partner,,
Phil, with his usual good-nature, provided
me with several of the figures used in this dissertation, in addition
to many which were not suitable for publication*
Of course, it is impossible to leave out the FOPS, whose col­
lective guidance, understanding, and peculiarities deserve mention*
Thus, I thank Mark Baumler, Mike Barton, Mary Bernard and Deb (Mad Dog)
Olszewski for whatever they did*
I also extend my gratitude to those
in the Old World Chapters, Professor Francois Bordes and Patty Anderson
in France, and Na'ama Goren in Israel, for putting up with my weird
ideas from time to time*
One cannot live on archaeology alone, however.
For free coffee
and advice I thank my friend and colleague Walter Birkby*
And for
providing needed diversions and love, I thank the girls in my life:
wife Leeland, and poopers Aggie, Bernie and Casey»
my
TABLE OF CONTENTS
Page
LIST OF TABLES
O
O
O
O
LIST OF ILLUSTRATIONS
lo
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
VI
o o e o e o e o o o o o o o o o o o o
ix
ABSTRACT o o o o o o o o o o o o o o o o o o o o o o o o o o
XII
INTRODUCTION
oo o o
1
The Interpretation of Lithic Variability o o o o o o o o
Problems of Interpretation o o o o o o o o e e o o o o o
Discovering the Meaning of Lithic Variability o o 0 o o
5
14
16
O
o oo
O
O
O
O
O
2o THE TABUN COLLECTION • • e o •
o o oo
O
* • oo
3o TECHNOLOGICAL FACTORS IN BASICFLAKE
O
O
o o o
O
o „. o o o o o „ o o
24
PRODUCTION , 0 o o o » o
55
The Evidence from Controlled Experiments o o o o o o o o
Comparisons with the Tabun Materials o o o o o o - o o o o
56
?8
40 TECHNOLOGICAL STRATEGIES AT TABUN ' 0o o o • • . • o o * o ■o
100
5o SUMMARY AND CONCLUSIONS
» » o» o o » » 0 » o » o o o
133
GLOSSARY OF METRIC AND NON-METRIC OBSERVATIONS»
140
METRIC AND NON-METRIC OBSERVATIONS 0 » o o » »
3
LIST OF REFERENCES o o o o o o o o o o o o o o o o o o o o o
150
APPENDIX I:
» o o
APPENDIX II:
v
157
LIST OF TABLES
Page
Table
Equivalence between Garrod's and Jelinek's stratigraphic
interpretation of Tabun » = = = = = . = « . = . = . = = = =
2?
2=
Basic inventory of Beds
90E1 and 90E2 . . . » = = = . . = =
35
3=
Type inventory for Beds
90E1 and 90E2 = . . . = = = = = = =
37
1,
40 Flake technique for Beds 90E1 and 90E2
= = = = = = = = = =
= = = = = = =
38
= = = = = = = = =
40
= = = = = = = = = =
40
5.
Basic inventory data for Beds 7611 and 76I2B
6o
Flaking technique in Beds 76II and 75128
7
Type inventory for Beds 7611 and 76I2B
°
37
8 „ Basic inventory data for Beds 75S1 ("Upper" Yabrudian) and
82BS and 82BI ("Lower" Yabrudian) = = = = = = = = = = = = =
41
Type inventory for Beds 75SI ("Upper" Yabrudian) and 82BS
and 82BI ("Lower" Yabrudian) = = = = = = = = = = = = = = =
43
10 c Flaking technique for Beds 75SI ("Upper" Yabrudian) and
82BS and 82BI ("Lower" Yabrudian) = = = = = = = = = = = = =
44
9o
11 o
Basic inventory for Bed 7511
. = = « = = = = = . = = « = =
44
12=
Flake technique for Bed 7511
= . . = = = = = . = « = = = =
44
13 o Type inventory for Bed 7511 = = = = = = = = = = = = = = = =
47
14=
Basic inventory of Beds
711 and 72S = = = = = = = = = = = =
15-
Flaking technique for Beds 711 and 72S
47
= = = = = = = = = =
48
16= Type inventory for Beds 711 and 72S = = = = = = = = = = = =
50
17=
Basic inventory for Bed 66
= = = = = = = = = = = = = = = =
50
= = = = = = = = = = = = = = =
51
Type inventory for Bed 66 = = « = = = = = = = = = = = = = =
51
18= Flaking technique for Bed 66
19=
vi
vii
LIST OF TABLES— Continued
Page
Table
20 o
Basic inventory for Unit I = = = = = = = = = = = . = = = =
53
21 =
Flake technique for Unit 1 = = = = = = = = = = = = = = = =
53
22=
Type inventory for Unit I
= . = . = . = = = = = = = = = =
54
23=
Exterior platform angle by categories of flake termina­
tion in controlled experiment . . . o . = = = = = = = = =
64
Multiple regression for length with exterior platform
angle (EPA) and platform thickness (PT) for flakes pro­
duced in controlled experiment = = = = = = = = = = = = = =
71
Multiple regression for thickness with exterior platform
angle (EPA) and platform thickness (PT) for flakes pro­
duced in controlled experiment = = = = = = = = = = = = = =
73
Mean length and median platform thickness and R-squares
between length and platform thickness (r) by intervals of
exterior platform angle for flakes produced with constant
force in controlled experiment = = . = = . = « , = . = = =
75
27 = Flake length and thickness (in centimeters) for three
ball sizes
o o o = o o 6 o = o o = = = o = o = o = = = =
77
24.
23=
26 =
28 =
29=
30=
31=
32=
33=
Exterior platform angle by categories of flake termination
for samples from Tabun = = = = = = = = = = = = = = = = = =
81
Multiple correlations of exterior platform angle» platform
width and platform thickness with (A) length, (B) width,
and (C) thickness (Tabun sample) = = = = = = = = = = = = =
85
Partial correlations for length, width, and thickness with
exterior platform angle (EPA), platform width (PW), and
platform thickness (PT), controlling for two of the three
independent variables (shown in parenthesis) = = = = = = =
90
Standardized Beta coefficients of independent variables
for each dependent variable by Tabun industries = . = = =
92
Multiple correlations for (A) length, (B) width, and (C)
thickness for all blades for Tabun sample = = = = = = = =
94
Canonical correlation analysis of length, width and thick­
ness with exterior platform angle, platform thickness and
platform width (N — 31C) = = = = = = = = = = = = = = = = =
95
viii
LIST OF TABLES— Continued
Table
34,
35-
360
37-
Page
R-square values computed for flake width and platform
width and for flake thickness and platform thickness by
intervals of exterior platform angle . . . . . . . . . . .
97
Median platform width, platform thickness, and platform
area (platform width x platform thickness) by intervals
of exterior platform angle for Tabun . . . . . . . . . . .
98
Mean exterior platform angles for plain versus facetted
platforms . . . o . . . . . . . . . . . . . . . . . . . . .
10^
Flake thickness by platform shape . . . . . . . . . . . . .
109
380 Mean flake thickness broken down by intervals of platform
thickness and platform shape
. . . . . . . . . . . . . . .
109
Mean platform width broken down by intervals of platform
thickness and platform shape . . . . . . . . . . . . . . .
Ill
40.
Basic dimensional data for the eight samples from Tabun . .
114
41.
Basic platform data for the eight samples from Tabun
...
116
42.
Percentage of flakes with concave platform edges for each
of the eight samples from Tabun . . . . . . . . . . . . . .
119
Basic dimensional and platform data for Levallois flakes
from labun
.. — .
125
44.
Basic data for Levallois flakes from Tabun
. . . . . . . .
125
45-
Summary of results of discriminant function analysis of
Levallois industries using Levallois flakes only . . . . .
127
39-
43-
LIST OF ILLUSTRATIONS
Figure
lb
Page
Temporal change in mean and variance of Vfidth/thickness of
complete flakes from Tabun o o o o o o p o o o o o o o o o
33
Cumulative graph of essential count of Mugharan Acheulian
and Unit XIV material from Tabun
36
Cumulative graph of essential count of Upper Yabrudian and
Lower Yabrudian from Tabun 0 0 0 0 0 0 0 0 0 = 0 0 0 0 0 0
42
O
3o
O
O
O
O
O
O
O
O
O
O
O
O
4 0 Cumulative graph of essential count of the Amudian from
Tabun 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
5=
Cumulative graph of essential count of the Upper Mousterian, Lower Mousterian and Transitional Mousterian from
Tabun 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 = 0 0 0 0 0 0 0 0 0
60 Design of controlled experiment
0
0
0
0
0
0
0
0
0
0
46
49
58
7= Scatter diagram of relationship of Interior Platform Angle
with Exterior Platform Angle for flakes produced in con­
trolled experiment 0 0 0 0 0 0 0 0 = 0 0 0 0 0 0 0 0 0 0 0
63
■80 Scatter diagram of relationship of length (in centimeters)
with Exterior Platform Angle (in degrees) for flakes
produced in controlled experiment 0 0 0 0 0 0 = 0 = 0 0 0
66
9o Scatter diagram of relationship of length with Platform
Thickness (in centimeters) for flakes produced in con­
trolled experiment 0 0 0 = 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
67
10o Scatter diagram of relationship of length with Platform
Thickness (in centimeters) for one interval of Exterior
Platform Angle for flakes produced in controlled experi­
ment 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
68
11o Scatter diagram of relationship of length (in centimeters)
with Exterior Platform Angle (in degrees) for one interval
of Platform Thickness for flakes produced in controlled
experiment 0 0 0 0 0 0 0 0 0 0 0 = 0 0 0 0 0 0 0 0 0 0 0 0
70
IX
X
LIST OF ILLUSTRATIONS— Continued
Figure
12o
Page
Scatter diagram of length to estimated length (based on
exterior platform angle and platform thickness) in con­
trol la d experiment o o o o o o o o o o o o o o o o o o o
o
T2
13o
Scatter diagram of thickness to estimated thickness (based
on exterior platform angle and platform thickness) in
controlled experiment o . o o . o o » c « o » o < . o ' o o ’o
l4„
Scatter diagram of relationship of Interior Platform Angle
with Exterior Platform Angle (both measurements in
degrees) for sample of flakes from Tabun <,0 0 . 0 0 0 0 0
80
Scatter diagram of length (in millimeters) to estimated
length based on exterior platform angle, platform width,
and platform thickness for combined Tabun samples . . . .
87
Scatter diagram of width (in millimeters) to estimated
width based on exterior platform angle, platform width,
and platform thickness for combined Tabun samples » . « .
88
Scatter diagram of thickness (in millimeters) to estimated
thickness based on exterior platform angle, platform width,
and platform thickness for combined Tabun samples .
.
.
o
89
15o
l6o
17o
l8o Exterior platform angle on different core types
. . .
102
19= Two identical cores with flakes of different platform
thicknesses removed . . . . . . . . . » . . . = . » » „ 0
106
20 o
21o
22o
23°
„.
Scatter diagram of Platform Thickness with Platform Width
(in centimeters) for combined sample from Tabun . . . . .
107
Shape of exterior platform edge viewed toward the platform
surface (top) and from the side (bottom) o . o o o o o o o
108
Three-dimensional graph of mean values of length, width,
and thickness (in millimeters) of eight samples of com­
plete flakes from Tabun o . o o o o o o o o o o o o o o o
113
Three-dimensional graph of mean values of exterior plat­
form angle (in degrees), platform width, and platform
thickness (in centimeters) of eight samples of complete
flakes from Tabun o o o o o o o o o o o o o o o o o o o o
113
LIST OF ILLUSTRATIONS— Continued
Figure
24c
Populations of Amudian,Lower Mousterian,
terian Levallois flakes plotted according
discriminant scores using flake dimension
data alone o o o o o o o o o o o o o o o o
and Upper Mousto their
and platform
o o o o o o o
25o
Populations of Amudian, Lower Mousterian,
terian Levallois flakes plotted according
discriminant scores using additional data
knapping strategy o o o o o o o o o o o o
and Upper Mous­
to their
that reflects
o o o o o p o
ABSTRACT
The ability to interpret variability in chipped-stone artifacts
is fundamental to an understanding of past human behavior0
There are
four major factors that contribute to lithic variability, raw material,
technology, function and styleo
This dissertation addresses itself to
basic technological relationships that operate during the production of
lithic artifacts and the strategies employed by prehistoric knappers in
controlling them.,
Through the technique of controlled experiment, a number of
variables that affect flake dimension and other observable lithic
attributes are isolated and described0 A similar analysis is then per­
formed on artifactual material from the Paleolithic site of Tabun Cave0
These studies demonstrate that variability in flake form can be ex­
plained on the basis of observable characteristics of platform prepara­
tion*
In particular, the manner in which the knapper varies the
exterior platform angle, platform width and platform thickness have
predictable consequences on the resulting flake morphology*
The manner in which prehistoric knappers control the independent
variables of the platform is also discussed*
The Tabun collections
afford a unique opportunity to examine changes in these strategies
through time*
In addition, the author performs an exploratory study of
the Levallois industries of Tabun in order to examine other aspects of
variability and suggests possible interpretations concerning the
relationship between them*
xii
CHAPTER 1
INTRODUCTION
This dissertation presents an attempt to further the under­
standing of those technological relationships that operate during the
production of lithic (chipped stone) artifacts,.
Stated simply, the
word ’’technology" encompasses the attributes and processes, both be­
havioral and physical, that relate directly to the production of these
artifacts,,
Thus, technology includes the manner in which a stone is
struck, the sorts of implements employed, and the kinds of core prepa­
ration involvedo
It is well known that accomplished flintknappers,
through controlled variation of these technological factors, can
produce a wide range of formal variation in lithic artifacts.
By
observing those technological variables that are apparent on the endproducts of prehistoric knappers, archaeologists should be able to
achieve a better understanding of the technological strategies used in
producing those artifacts and thereby produce more meaningful interpre­
tations of archaeological assemblageso
A question could be raised concerning the overall importance to
archaeology of an understanding of flaking technologieso
If a primary
goal of archaeology is to discover why a tool was made, in other words,
what function it was intended to serve, then do we have to know the
details of how it was made?
1
2
There are several reasons why an understanding of lithic tech­
nological relationships is meaningful in archaeological research0
Technology is directly responsible for the production of the artifac­
tual evidence that constitutes the archaeological recordo
Since
different techniques of manufacture can produce different results,
an understanding of technological variability is basic to our under­
standing of artifact variability» Furthermore, an understanding of how
a particular technology is governed by other factors, including the
nature of the material and desired artifact function, as well as tra­
ditional choice, is basic to our interpretation of the artifactuai
recordo
The word "technology" can refer to many different aspects of
stone tool manufacture0
In the broadest sense, it is possible to
identify major technological methods, each of which incorporates a
variety of procedures and tools, such as biface, Levallois, or blade
production.
Sometimes these methods can be equated with particular
cultural traditions, as in the case of the Mesoamerican pressure-blade
technologyo
In another sense technology can refer to the physical
properties and dynamics of conchoidally fractured materials0 These
aspects of lithic technology are best understood through analyses based
on fracture mechanics.
In this dissertation the focus is on the identification of some
technological strategies that have been used to control flake dimensions.
In order to do this, it has been necessary to isolate and describe some
basic relationships that exist between the actions performed by a
flintknapper and their effects on the object being flaked.
Thus,
throughout this dissertation the word technology is used to refer to a
set of relationships that operate during the actual process of flintknapping =
It is the purpose of this study to describe the manner in
which a flintknapper can control and, in fact, take advantage of those
relationships in order to obtain particular results0
This dissertation is not intended to be a manual for the modern
flintknapper; instead, its focus is on how the analysis of existing
(ic.e0, archaeological) artifacts can be designed to reconstruct tech­
nological strategies used by prehistoric flintknappers0
The lithic
materials used in this study were from collections obtained by Arthur
Jo Jelinek during his excavation of Tabun Cave, an early Upper Pleis­
tocene site located near the northern coast of Israel (Jelinek et al0
1973)o
The basic organization of this dissertation is as followso
Chapter 1 presents a brief discussion of several topics that relate to
the interpretation of lithic artifacts0 First is a review of the major
underlying factors contributing to lithic variability.
raw material, technology, function, and style0
Among these are
It is emphasized that
perhaps the single most important goal in lithic studies is to achieve
a better understanding of the effects of each of these factors on par­
ticular aspects of the artifacts themselves.
Toward this end several
methods of specific kinds of studies are now being used by archaeolo­
gists and these Eire briefly reviewed.
Primarily, this chapter attempts
to place the present study in the context of general lithic research.
Chapter 2 presents a brief review of the excavations at Tabun,
as well as a basic description of the industries from which the samples
used in this analysis were derived*
While the excavations undertaken by
Professor Jelinek have already contributed significantly to our under­
standing of this area (Jelinek 1980), his analysis of the materials has
not yet been completed*
Thus, at this stage of the research it was
decided to emphasize the methodological aspects in this study rather
than to emphasize the place of the particular results in the context of
a current synthesis*
This latter aspect of the research will be in­
cluded in a section by the author in the final report on Tabun*
Chapter 3 is, in many ways, the most important chapter in this
dissertation*
Given a process as complex as flintknapping, it is
initially difficult to isolate technological relationships under any­
thing but controlled conditions*
In this chapter there is a review of
results obtained from previous controlled experiments in flake produc­
tion (focusing on those performed by the author)*
These experiments
have isolated particular relationships that can be controlled during
lithic manufacture*
Using these data, a comparison is made between the
results obtained under controlled conditions with-those obtained through
an analysis of the Tabun material*
This chapter is important for two reasons*
First, the condi­
tions under which the controlled experiment was performed permits the
technological relationships to be quantified and expressed objectively*
This, in turn, leads to more objective evaluations of relationships
between particular variables*
Second, the comparisons with the arti-
factual material not only are a means of evaluating the experimental
results, but are also of use in isolating some of the interpretive
limits of controlled experiments*
During this discussion a major
5
distinction is drawn between the independent variables that are con­
trolled by the flintknapper, and the dependent variables that are.
reflected in the final result*
reconstruction
This distinction is important for the
of past flintknapping
Chapter 4
strategies*
is a discussion of specific strategies employed in
the production
of the separate Tabun
can be defined
as a method or a series of maneuvers for obtaininga
specific goal or result*
industries*
The word "strategy"
In the context of lithic production, this
series of maneuvers is represented by the manner in which the flintknapper controls his independent variables, and the results are
reflected in the expression of the dependent variables*
It is on the
basis of both sets of variables that the separate Tabun industries are
compared*
Chapter 5 summarizes the major findings of this study and sug­
gests particular directions for future work*
It must be emphasized
that the purpose of this dissertation is to demonstrate the existence
of particular relationships that exist during flake manufacture*
Supplemental information is presented in the two appendices*
Appendix I provides definitions of the metric and non-metric observa­
tions used in this study*
Appendix II is a list of these observations
for the Tabun samples*
The Interpretation of Lithic Variability
Lithic artifacts form a large part of the archaeological data
base*
In paleolithic archaeology in particular, chipped stone tools
and debitage are the most important single source of information*
They
are used, among other things, to identify culture groups and their
temporal succession (e0go, Hordes 1961; de Sonneville-Bordes 196.3)» to
describe functional activities (eogo, Cohen, Keeley and van Nooten 1979;
Klein 1977), and as evidence for certain aspects of biological evolution
(e„go» Krantz I960; Watanabe and Kuchikura 197*0°
Primarily, the study of lithics proceeds by the examination of
formal characteristics of the artifacts, such as size, shape, modifi­
cation, and material0 Variability among these attributes is a result
of a number of factors acting simultaneously during the production of a
lithic assemblage = Differences in raw materials, such as quantity,
quality, and accessibility, play a role because they often limit the
potential range of variability in a lithic assemblage°
Few would con­
test the proposition that pressure blades cannot be made on basalt, or
that large bifaces cannot be made on small river pebbles°
But the
effects of raw material differences can play a subtler role*
For
example, Fish (1978) was able to show positive correlations in the Near
Eastern and European Mousterian between the size of locally available
flint nodules and the size of complete flakes, and between local raw
material size and the emphasis on Levallois technique°
Similarly,
Munday (1976) suggests a relationship between flake size and distance
from recognized outcrops of material for several Mousterian assemblages
in the Negev desert °
It is clear then that an understanding of certain kinds of raw
material variability is important to an understanding of certain
aspects of artifact variability0 What is not clear yet, however, is
precisely which variables of raw material are relevant to particular
lithic technologies, and which are related to artifact function.
Texture,
for example, is often an important consideration in applying a particu­
lar technique such as pressure-flaking.
On the other hand, highly
brittle materials (e,g,, obsidian) are not well-suited to tasks such as
chopping.
ships,
More work will be needed to further clarify these relation­
There may even be stylistic criteria involved in the choice of
raw material (Styles 1979b), although this has yet to be convincingly
demonstrated,
A second important factor affecting lithic variability is func­
tion, i,e,, to what specific tasks the finished artifact will be
applied.
As a factor contributing to lithic variability, artifact
function is important since it seems clear that stone tools, particu­
larly retouched pieces, were manufactured or modified in order to carry
out particular tasks, However, in spite of the work with microscopic
examination of tool edges (Semenov 1964; Tringham et al, 1974; Keeley
1978a, 1978b), functional variation in artifact form is still limited
to very gross evaluation.
In an unpublished paper, Jelinek (1975) has outlined some of
the basic variables that contribute to functional variability.
These
include the nature of the resources exploited, the nature of the
exploitative activities (i,e,, the type of actions in which the tool
was involved), and the functional design of the artifact (including
size, shape, hafting modification, etc,).
However, our ability to
recognize these variables is further complicated by what Jelinek (1976)
has termed the "Prison effect," in which a single piece may go through
several stages of different uses with concomitant modification of its
formal properties« Thus, an artifact subjected to such a process is
likely to exhibit some morphological characteristics of an earlier stage
which may be irrelevant to our understanding of its final use0
Style, because it represents a choice among functionally equiva­
lent forms (Jelinek 1975? see also Sackett 1973» 1977) is also an
important factor contributing to lithic variability..
It is also one
that is difficult to isolate in the archaeological recordo
There is no
doubt that the recognition of stylistic variability is important to
most interpretations of culture history:
quite often the basic units
of analysis in archaeological research are social groups, which by
analogy with modern societies may have followed certain traditional or
cultural rules in producing stone toolso
The ability to recognize such
groups in the prehistoric record depends, for the most part, on the
ability to recognize stylistic attributes of the artifacts themselves=
To date, those lithic studies which have dealt with this factor have
not been entirely convincing, particularly those concerned with Paleo­
lithic materials (Close 1978; Ohel 1979; Styles 1979a)o
There may be several reasons for this failure, but at least a
major part of it is due to the nature of the evidencec
A large portion
of any lithic assemblage consists of simple flakes with only minor
modificationSo
As will be made clear in the following chapters, the
production of these flakes, and the nature of their attributes, is
largely dependent on technological factors,.
It is through more exten­
sive modification that personal Or cultural variation may have its most
obvious effects0 The stylistic variability that is exhibited among
different types of projectile points, for example, is apparent only
because of this modification.
Among unmodified pieces, differences in
style are indicated only when the technology being applied is unique,
such as Mesoamerican pressure blade production.
It could be argued that technology is not a distinct factor, of
lithic variability, but rather an indirect reflection of the other
factors.
In other words, a particular technology is employed because
of the raw material used, or because of particular functional require­
ments, or perhaps because of stylistic choice.
In the production of a
lithic assemblage this argument is essentially correct.
However, when
the problem is one of interpreting a given lithic assemblage, an
analysis, and understanding, of technological aspects is often quite
important.
This is because there is not direct correspondence between
technology and the other factors of lithic variability.
Many different
technologies, or flaking techniques, can be employed to produce func­
tionally equivalent pieces on the same raw material.
In this case,
variability would exist primarily on the technological level, Tech­
nology would then be the primary base for comparison (see Sheets 1975)o
The role of technology for interpretation will be discussed further in
following sections.
In addition to raw materials, technology, function, and style,
there are several other factors contributing to lithic variability which
are either of minor importance, or whose effects are difficult or im­
possible to assess.
One of these is variations in basic ability of the
individual flintknappers,
It is important to bear in mind that although
an expert has the potential to produce different (1,6,, ’’better’1)
results than the beginner, he does not always do so, and therefore the
10
ability of the knapper may not be consistently evident in the artifacts
themselves*
No matter what the ability of the knapper, error is another
factor affecting his results*
Because lithic production is a reduction
process, error can have serious consequences with regard to the form
of the finished product*
The same is true for minor and unpredictable
imperfections in the raw material* .
Although directly related to the mechanics of lithic production,
these minor factors are not generally considered to be part of the
technological variability exhibited within lithic assemblages*
Pri­
marily this is because it is difficult to control for such factors of
variability in the course of a lithic analysis*
Thus, one normally
assumes that their effects are minimized or relatively constant in the
production of an entire lithic assemblage*
These factors of lithic variability have been discussed at some
length in the literature (see especially Binford 1963; Jelinek 1975;
and Rick 1980) and only a few points are necessary to repeat here*
It
is clear that in the production of a lithic assemblage, or even a single
artifact, all of these factors interact simultaneously in determining
particular aspects of the finished products*
The choice of a raw mate­
rial, for example, which is often dependent upon availability, may also
be governed by functional or stylistic criteria*
But, given a particu­
lar raw material, there are limitations imposed on the technology
employed as well as functional and stylistic modifications*
Because
of the interaction of these factors, the determination of fundamental
explanations or interpretations concerning lithic variability becomes
very difficult*
11
This interpretational problem is made clearer with a hypotheti­
cal exampleo
Suppose that there are two sites in a region, one of which
contains large handaxes and the other small chopping toolso
Let us also
imagine that the site with handaxes is located near a source of large
nodular flint
from which the handaxes were made*
On the other hand,
the choppers at the other site were made from local quartzite gravelso
There are several possible interpretations for the differences in
artifact types between the two sites0
lo
The two sites contain different tools because of the differences
in available raw materialso
Large handaxes are impossible to manu­
facture on small gravels, and so the inhabitants at the latter site
simply modified their technology accordingly=
2o
The sites differ because different functional activities were
performed at eacho
Based on the lithic formal differences alone, and
in the absence of other kinds of information such as faunal remains,
this interpretation cannot be ruled out*
3o
The two sites were occupied by two different cultural groupso
This interpretation also cannot be ruled out solely on the basis of
the lithic assemblage =
Although usually more complex, this is the type of problem that
archaeologists most commonly face 0 Variability among lithic assemblages
is the most basic fact that demands archaeological interpretation0 When,
as is the case in the above example, there are several possible inter­
pretations of that variability, we must have some way of deciding which
interpretation is most accurate0
12
For purposes of analysis and interpretation, there is one
important means of doing this0
Although at the time of manufacture all
of the factors affecting lithic variability operate simultaneously, it
is sometimes.possible for the archaeologist to control (i0e0, hold
constant) one or more of them0
This is an important means of isolating
the effects of particular factors,.
If the observed patterns of vari­
ability continue in spite of the controlled value of a particular
factor, then it is possible to eliminate that constant factor as a
cause of the variability0
To show how this works, we can return to the hypothetical
example presented above„
In this case, it might be possible to control
for raw material variability by locating other sites that were not so
restricted in terms of locally available raw materials<> For example,
if a chopper site were found in an area of large flint nodules, the
conclusion would be that the raw material did not dictate the manu­
facture of one or the other type of implement0
The factor of function can also be controlled in a similar
fashiono
Ideally it may be possible to determine (through microscopic
wear patterns or faunal analysis) that the activities carried out at
each site were identical=
If this were the case, then it should be
clear that function could be eliminated as a factor in determining the
observed tool type variability=
If both function and raw materials
were eliminated, then a stylistic interpretation could be supported
through a process of elimination (see Close 1978 for an example of this
kind of reasoning) =,
13
Another major point concerning these factors of variability is
that they are mesuit to be understood as factors affecting lithic vari­
ability smd not as reasons for differences in behavior=
In other words,
the factors contributing to a particular behavior should be distin­
guished from the factors which directly affect the variability in the
stone artifacts themselveso
Unless this distinction is made, archae­
ologists run the risk of talking past each other in offering interpre­
tations or explanations of specific examples of lithic assemblage
variabilityo
As an example of this it is possible to refer again to the
hypothetical sites presented earlier= Given in situ manufacturing
activities at the handaxe site, it would not be surprising to find a
large number of bifacial retouch flakes there =
Their presence would
not be explained in terms of function or styleo
The presence of bi­
facial retouch flakes is due solely to the use of bifacial technique;
this is a technological explanation for their presencec The reason
why the handaxes themselves were made, ioe0, what gave rise to that
particular behavior, has no direct explanatory relationship to the
presence of these flakeSo
This distinction between the factors directly affecting lithic
variation and those which affect differences in behavior is quite
importanto
It can be argued that an understanding of what gives rise
to behavioral differences is the ultimate goal of archaeological re­
search =
The point here is that the expression of behavior in stone
artifacts may be modified by such factors as raw materials and tech­
nology,
Likewise, the expression of function and style are modified
14
according to the limitations of the medium itself =. Thus, to understand
behavior through the analysis of lithic artifacts it will first be
necessary to understand how those factors operate that directly affect
that lithic evidence„
Problems of Interpretation
A lack of understanding of the operation of these factors on
lithic formal variability can lead to several problems in the interpre­
tation of lithic assemblages=
This is true regardless of the particular
kind of analysis being performed0
There has been a traditional emphasis on typological analysis
in paleolithic archaeology, going back to the work of Lubbock and
de Mortillet in the 19th century.
There are several major typologies
in current use for paleolithic materials, that of Bordes (I96lb)i Clark
and Kleindienst(1974), M, Leaky (1971)9 and de Sonneville-Bordes
and Perrot (1954-1956)°
Within each of these typologies, a particu­
lar type represents a specific cluster of pre-defined attribute states.
In other words, the members of each type class share a distinct group
of characteristics.
These categories are useful for descriptive purposes, but beyond
the level of descriptive comparisons the interpretive utility of a
typology is dependent upon our understanding of how each of the defining
characteristics is affected by the factors of raw material, technology,
function and style.
In fact, within most typologies each of the type
classes are influenced differently by these four factors.
When this
is the case, the typology as a whole reflects all of them simultaneously,
15
and thus it is difficult to go from typological variability alone to an
interpretation of the causes of that variabilityo
This difficulty will
continue until the introduction of typologies in which the morphologi­
cal criteria for all type classes are understood in terms of these four
factors, and the typologies are designed so that each addresses par­
ticular questions (see Jelinek 1975)o
Within the last two decades there has been a marked increase in
the use of statistical analysis for the testing of explanatory hypothe­
ses in lithic research.
The application of statistical techniques and
concepts also requires an understanding of the causes of lithic vari­
ability.
For example, consider that a hypothesis is proposed concerning
a particular aspect of past behavior. To test this hypothesis, it is
necessary to develop test implications, i.e., predictions regarding
certain attributes of the artifacts themselves which are logically
derived from the hypothesis.
In lithic analyses, these test implica­
tions are stated in terms of the lithic variables used in the analysis,
whether these variables are typological classes or the individual
attributes themselves.
The tests generally take this forms
"If a
particular event (i.e., the hypothesized behavior) occurred, then it
will be reflected in the values of those lithic variables selected as
test implications."
Thus, by observing those variables and through the
application of the relevant statistical techniques, it should be pos­
sible to determine within the limits of statistical probabilities
whether or not the hypothesized event occurred.
16
It should be clear, however, that in choosing those variables to
be used as test implications for a given hypothesis, there must be prior
knowledge of their meaning (ioe0, what factors these variables reflect)
and relevance (ioe0, their logical relationship to the hypothesis in
question)0 If the variables chosen as test implications for the
hypothesis are not relevant, or if their meaning is not completely
understood, then the test results are, at best, equivocal.,
As was the
case in typological interpretation, the use of statistics for the test­
ing of explanatory hypotheses is limited by our understanding of the
meaning of particular lithic attributes..
This is not meant to be a criticism of the goals of either
typological analysis or hypothesis testing..
The question being raised
here concerns the ability to use these methods to their maximum poten­
tial given that little is known of how the factors affecting lithic
variability operate.
It is suggested that many of the arguments that
have centered on the interpretation of particular industries are the
result not of the analytical methods that were employed but rather the
lack of knowledge concerning the causes of the lithic variability in
terms of these four factorso
Discovering the Meaning of Lithic Variability
It should be clear from the preceding discussion that one of
the major goals of lithic research is to understand the meaning of
observed variability in terms of the factors which directly contribute
r
to it0 Toward this end archaeologists have, up to the present, relied
on four basic methods for discovering the meaning of lithic attributes.
17
These are ethnoarchaeology, replicative experiments» controlled experi­
ments, and statistical analysis*
This section will briefly review these
methods in order to place in context the analyses that will be presented
in later chapters*
Ethnoarchaeology provides the only direct source of information
concerning the role of stone tools in a cultural context, and recently
there have been a number of attempts to take advantage of it (Ebert
1979; Gould, Koster and Santz 19711 Gallagher 1977)° The basic purpose
of ethnoarchaeology is to provide present day analogies for the inter­
pretation of prehistoric artifacts*
A major question that is raised regarding ethnoarchaeological
analogies concerns the relevance of these analogies to situations that
existed in the past*
Societies still relying on chipped stone arti­
facts, and thus having the potential to explain their lithic technology
to us, are becoming quite rare*
Furthermore, in terms of refinement
and complexity, these groups usually exhibit technologies that are not
entirely comparable to prehistoric assemblages*
For example, there are
no existing groups that utilize bifacial techniques similar to PaleoIndian, or Acheulian, and the same is true for specialized techniques
such as Levallois, pressure blade production, or fluting*
Thus we are
already beyond the point where it would be possible to gain certain
kinds of knowledge concerning the role of lithic technologies within
the context of on-going cultural systems*
Beyond the lack of particular formal resemblance, these mate­
rials in all probability do not assume as great an importance (either
emotional or, primarily, utilitarian) to the people in present
18
societies as they may have in the past.
This is due to the fact that
even within these so-called Stone Age societies, there has been exten­
sive replacement of stone tools by more modern technologies (Sharp 1956;
Gallagher 1977)°
There is little doubt, then, that there are definite
limits as to the significance of the analogies which are producedo
Nonetheless, there have been relatively few ethnoarchaeological
attempts to deal specifically with the factors affecting formal varia­
tion directly, which is the kind of variation we are concerned with
here°
Instead, the emphasis in most of these studies has been on either
the observed use and production of stone tools (Miller 1979; Carneiro
1979)» assemblage distributional variability (Hayden 1978), or disposi­
tional processes (Gallagher 1977)°
Because it is sometimes impossible to find ethnographic
examples of particular techniques in working stone, it becomes neces­
sary for the archaeologist to reproduce experimentally the techniques
that can be employed to produce particular results«
These kinds of
experiments, termed replicative experiments, have a long history in
lithic studies (see Johnson 1978)o
It is perhaps accurate to say that
there are flintknappers living today who have at their command more
techniques in chipping stone than any single prehistoric flintknapper°
While this is good for obtaining an understanding of many extinct
knapping strategies, it may also lead to biases in interpretation.
Replicative experiments are useful for a wide range of problems
and there are examples that have been concerned with each of the fac­
tors affecting lithic variability (Iverson 1956; Gunn 1975; Crabtree
1966, 1967)° But overall, the most frequent factor studies in
19
replicative experiments is that of technology (e0g0, Bordes and Crab­
tree 1969; Bradly, Henry and Haynes 1976; Crabtree 1970; Jelinek,
Bradley and Huckell 1971) =
As is the case with ethnoarchaeology, replicative experiments
provide analogies to past situations.
In many replicative studies
there is an implicit assumption that if a technique is found that pro­
duces a certain result, then it must correspond to the technique used
in the past.
However, as Crabtree's (1966) study of Folsom point pro­
duction has demonstrated, it is sometimes true that more than one
technique can be found to produce the same results (see also Flenniken
1978)o
It is thus difficult to use replicative experiments alone to
test whether or not a particular technique was used by aboriginal
flintknappers •— replicative experiments merely suggest techniques that
could have been usedo
However, the probability that a particular technique was used
in the past increases as the results of the experiment, at each stage
of manufacture, conform to the archaeological materials.
In other
words, all aspects of the production sequence (including the "by­
products") must be duplicated as well as the morphology of the finished
piece.
In fact, these by-products often allow an understanding of pre­
historic strategies in the absence of the finished forms.
In spite of
their limitations, replicative experiments give us an intuitive under­
standing of flintknapping strategies that may in turn help us to
develop more meaningful explanations of prehistoric lithic variability.
Controlled experiments, in which several variables are isolated
or held constant, offer an even more objective means of determining the
20
effects of various factors on lithic attributes.
Moreover, they allow
for the isolation of certain variables, permitting us to obtain a clearer
understanding of their relationships to each other.
To date there have
been controlled experiments undertaken to determine the effects of
variation in raw materials (Bonnischen 1977), technology (Speth 1972,
197*+, 1975; Dibble and Whittaker in press), and function (Semenov 1964;
Tringham et al, 197*+) ° Because of their nature, considerations of
stylistic variability are difficult to design into such experiments.
Controlled experiments are, of course, somewhat artificial,
both in their operation and sometimes in their results.
For example,
this author (Dibble and Whittaker in press) dropped ball bearings on .
glass cores in order to produce flakes.
This is obviously an improbable
mode of flintknapping in aboriginal societies.
Moreover, in many re­
spects the experimental flakes did not resemble flakes produced by
traditional methods, .To some extent the artificial nature of such
experiments can make it difficult to extrapolate from the experimental
results to actual archaeological problems.
The question of relevance
will be more fully addressed in Chapter 5 and at that time it will be
demonstrated that controlled experiments enable one to identify and
describe relationships that are too complex.to analyze through other
methods.
It was emphasized earlier that there are severe problems in
using lithic materials for the testing of explanatory hypotheses.
How­
ever, existing collections may be used to find interpretable associ­
ations between variables in what is called exploratory analysis.
Basi­
cally, exploratory analysis searches for statistical relationships
21
between lithic attributes as a means of suggesting cause-and-effect
relationshipso
As such, this kind of analysis represents a fourth
method for discovering the meaning of lithic variability, and one that
works in the context of prehistoric lithic assemblageso
Such an approach contrasts with hypothesis testing on a number
of important points„ Unlike explanatory hypothesis testing, exploratory
analysis does not require the prior knowledge of the meaning of all the
variables involved.
In fact, the discovery of such meaning is its goal.
As such, variables are examined in order to find relationships that may
exist between them, and they are not test implications of an explanatory
hypothesis.
It is true that a hypothesis is involved in the analysis —
that there is an association between certain variables —
but this
hypothesis is only the alternative of the statistical null hypothesis
and is not, in itself, explanatory.
In other words, the results of an
exploratory analysis may lead to the generation of hypotheses (in the
form of interpretations), and are not tests of pre-existing hypotheses.
As always, the validity of the actual statistical methods employed in
the exploratory analysis have direct bearing on the accuracy of the
proposed explanations.
But no matter how valid the statistical method­
ology, the result is still only a hypothesis which should be indepen­
dently tested.
There are several examples of exploratory analysis (although
they are usually couched in terms of hypothesis testing)
It is prob­
ably fair to say that the so-called Bordes-Binford controversy (Bordes
1973; Binford and Binford 1966) is entirely based on hypotheses gener­
ated through exploratory analyses,
Bordes, having found certain
22
patterns in his data of Mousterian assemblages from France and the Near
East, suggested an explanation involving cultural groups» These groups,
of which there are four, were defined on the basis of varying fre­
quencies of certain types of retouched tools and presumably followed
different lifewayso
The Binfords, after applying different statistical,
methods on the same data, offered an alternative explanation involving
differences in functional activities being performed during the depo­
sition of these assemblages»
The problem of Mousterian variability has,
in fact, been looked at in a number of different ways (see, for example,
Mellars 1973 5 Collins 1970)»
But the point here is that these proposed
explanations are hypotheses generated on the basis of exploratory
analyseso
As stated earlier, their confirmation must wait until enough
information is obtained regarding the meaning of the observed vari­
ability and more appropriate tests appliedo
To summarize, it is clear that a major goal in lithic studies
is to gain a better understanding of the factors contributing to vari­
ability,
Basically there are four such factors:
nology, function, and style.
raw material, tech­
All of these interact simultaneously in
the production of most lithic attributes and in all artifact assemblages,
and this interaction makes it difficult to isolate the effects of any
one ,
In the following chapters attention will be focused on particu­
lar aspects of technological variability.
The purpose of these analyses
will be to discover the meaning of particular lithic attributes, pri­
marily flake dimensions, in terms of technological variation.
These
analyses will depend primarily upon two of the methods discussed above,
controlled experiments and exploratory analyses of the Tabun collections.
As an introduction to this study, it is first necessary to discuss the
specific samples that have been analyzed and the site from which they
were excavated,
CHAPTER 2
THE TABUN COLLECTION
The lithic materials that provide the basis of this study come
from the site of Tabun, a cave located in northwest Israel near the
Mediterranean coast«
Situated on the south side of the mouth of the
Wadi Mughara on the western edge of Mount Carmel and overlooking a
large coastal plain, the site affords access to several environmental
zoneSo
site:
Such a location must, in part, account for the richness of the
Jelinek
(in press)
estimates that Tabun originally contained
perhaps as many as 1»4 million artifacts in over 24 meters of deposito
In the same Wadi, and adjacent to Tabun, are the sites of Skhul and
El Wado
Together they span a period covering the entire upper Pleis­
tocene and early post-Pleistocene 0
Tabun, along with Skhul and El Wad, was originally excavated by
Professor Do A» E= Garrod between 1929 and 1934 (Garrod and Bate 1937)°
In a manner typical of that era of paleolithic archaeology (see, for
example Neuville 1934; Coon 1957)» Garrod, in this five year period,
excavated approximately 2,000 cubic meters of the siteo
From this
excavation she save$ around 55,000 artifacts (mostly untouched tools)o
Several ’’layers” were defined primarily on the basis of typology, espe­
cially scraper and hand-axe forms« These were, from top to bottom:
Chimney I and II and Layer B, which Garrod termed Upper LevalloisoMousterian; Layers C and D, Lower Levalloiso-Mousterian; Layer E
24
25
(subdivided into Ea through Ed), a heterogeneous series collectively
labeled Micoguian in the original report; Layer F, with an Upper
Acheulian industry; and Layer G, originally called Tayacian0 Contrib­
uting to the importance of the site was the fact that among the finds
were a number of hominid remains, including a nearly complete meanderthaloid skeleton originally assigned to Layer C (McCown and Keith 1939)»
Given this long sequence of rich and stratified industries,
Tabun has, since Garrod's excavation, served as a standard for organ­
izing and comparing Upper Acheulian and Mousterian collections derived
from the entire eastern Mediterranean region.
Based on this sequence,
and on materials derived from other sites in the area, several workers
have developed syntheses of Near Eastern prehistory (Howell 1959;
Skinner 1965; Perrot 1968; Copeland 1975)° These syntheses have, for
the most part, substantially modified Garrod’s original interpretations
of the cultural sequence.
Perhaps the most fundamental evidence relating to interpreta­
tions of this portion of the Levantine sequence has come from the
recent re-excavation of Tabun by Professor Jelinek '(Jelinek et al.
1973)o
The primary reason for excavating the site a second time was to
apply more modern excavation techniques in order to obtain a more accu­
rate picture of the depositional history.
This is, in fact, part of an
important trend in the area that includes the re-excavation of Jerf Ajla
by Schroeder (1969), Qafzeh by Vandermeersch (1966), Ksar Akil by Tixier
(1963)» and Yabrud by Solecki (1970).
Jelinek’s excavation proceeded inward from the profile left by
Garrod, thereby allowing him to sample nearly all the horizons noted
by her, with the exception of Layer F c During his five year excavation
(1967-1971) 9 a little over 44,000 artifacts greater than 2<>5 centi­
meters in maximum dimension were removed from about 90 cubic meters of
deposito
Unlike Garrod, Jelinek paid maximum attention to geologic
evidence in defining stratigraphic intervals0 These intervals are
based on two levels of distinction.
The first level defines Major
Strati graphic Units, which are separated from each other by evidence
of major geologic disconformity.
As such, each of the units represents
substantial periods of more-or-less uniform sedimentary deposition
followed by periods of stability.
There were 14 such units in that
portion of the cave excavated by Jelinek.
Garrod’s layers are shown in Table 1.
The relationship of them to
The more restricted strati­
graphic intervals within these major Units are termed individual Beds,
that is, distinct geologic contexts within the major Units.
In addi­
tion, most of the beds were further subdivided on the basis of artifact
concentrations that were distinguished by the horizontal and vertical
back-plotting of artifact positions.
Altogether there are a total of
309 separate artifact bearing contexts defined in Jelinek’s sequence.
On the basis of the materials recovered during the excavation,
Jelinek (personal communication 1980) is able to offer a detailed
description of the Tabun sequence.
Unit XIV, the equivalent of which was called Tayacian by
Garrod and "Tabunian” by Howell (1959), is actually composed of ten
separate artifact contexts in Bed 9°°
In terms of typology, the unit
as a whole appears to be quite homogeneous.
Geologically it is com­
posed primarily of aeolian beach sand, which suggests the proximity of
27
Table 1„
Equivalence between Garrod's and Jelinek* s stratigraphic
interpretation of Tabun.
Garrod
Layers
Jelinek
Major Units
I
1-26
II-VIII
27-61
Bottom B; C
Layers C-D
Layer D
Beds
IX
62-69
Layer Ea
X-XI
70-77
Layer Eb (?)
XII
78-80
Layer Ed (?)
XIII
81-85
Layer G
XIV
90A-90J
(Jelinek, personal communication 1980)
28
a high sea stand at the time of deposition, probably equating with the
earliest part of the last interglacial cycle (Jelinek et al. 1973;
Farrand 1979)o This temporal position, and the presence of bifaces
(ca0 3-5 percent throughout the unit), suggests that it should be de­
noted culturally as a generalized Upper Acheulian, although it is in
many ways distinct from the succeeding Acheulian industries (Jelinek
1980)0
Perhaps when similar 'Tayaclan’^like collections from lower Oumm
Qatafa, Pas Beirut II and Yabrud IV (Hours et al 0 197*0 are re-examined
they likewise can be assigned to an Upper Acheulian culturec
In Jelinek*s stratigraphy, Units XIII, XII, and XI correspond
to Garrod*s Layer E and appear to have been deposited during the last
interglacial and perhaps into the time of a major sea retreat (Farrand1979; Jelinek et alo 1973)■>
Unlike Unit XIV, these units are typologi-
cally highly variable, a fact noted by Garrod in her subdivisions of
this "Layer" (Garrod 1956)o Three major industrial manifestations can
be isolated:
Acheulian, Yabrudian and what has been called either Pre-
aurignacian or Amudian (Rust 1950; Garrod 1962; Garrod and Kirkbride
1961; Copeland 1975)o
The Acheulian and Yabrudian are distinguished primarily on the
basis of different frequencies of two major tool categories:
and scraperso
bifaces
Characteristically the Acheulian has higher frequencies
of bifaces and relatively few retouched tools.
What may be related
Acheulian forms come from several sites in the area, such as Oumm
Qatafa, Yabrud, Kissufim, and Evron (Gilead 1970; Reliefson 1978; cf,
Perrot 1968),
On the other hand, the Yabrudian, which occurs also at
Yabrud, Bezez, Zumoffen and perhaps Zuttiyeh (Copeland 1975; Gisis and
29
Bar-Yosef 197^), has few or no bifaces and high frequencies of re­
touched pieces, mostly scrapers*
Although particular scraper types
(e0go delete, transverse and simple convex types) have been suggested
as being particularly characteristic of the Yabrudian (Bordes 1955;
Rust 1950), Jelinek (1980) has shown that at least within the recent
Tabun collections, these forms appear in similar ratios throughout
the relevant units regardless of industrial assignment*
The Amudian is a somewhat peculiar industry, consisting of
relatively few retouched tools and bifaces, and higher concentrations
of prismatic blades*
Those retouched pieces that do occur are quite
often Upper Paleolithic elements, especially burins and backed knives*
Although Garrod (1956s 47) has stated that the Amudian occurred in
three layers, this industry appears to occur only once in that portion
of the cave excavated by Jelinek,
The relationships between these three industries have not,
until now, been fully understood*
Clearly they do not represent a
temporal succession, for they are often found inter-strati fie d * At
Tabun, for example, there are two major occurrences of Yabrudian,
separated by several occurrences of Acheulian and the Amudian*
De­
spite its precocious nature, even the Amudian is not particularly late
in the sequence, having been deposited well before the Mousterian and
in fact preceding late occurrences of both the Yabrudian and Acheulian*
Based on recent analyses, Jelinek (personal communication 1980)
presents a strong case that the late Acheulian, Yabrudian and Amudian
are all facies of a single major tradition*
This tradition, called the
Mugharan Tradition, appears to vary in response to certain climatic
30
conditions, with the extreme forms of this variation being what com­
prise the three major facies as they are typically defined^,
The evi­
dence for such industrial continuity is as follows<,
As was just noted, the major difference between the Acheulian '
and Yabrudian is most basically expressed in terms of the emphasis on
biface or scraper production, respectively.
However, when examined
throughout the sequence, it is clear that the relationship between bi­
face to scraper frequency is cyclical in nature with definite "transi­
tional” industries between each of the extremes.
Such gradual and
repeated changes would be unlikely if the various industries were the
result of different populations moving into the area at different times.
More likely these changes reflect gradually changing conditions, and in
fact they appear to correspond with major climatic changes, as evidenced
by geologic events in the Tabun cave (such as subsidence and/or marked
changes in sediment deposition) and temperature changes in the oceans
(as reflected by oxygen-isotope changes
/Emiliani and Shakleton 1974/)»
Thus, within the Tabun sequence it is possible to see the Yaburdian
occurring in times of maximum warm periods with high sea level, and the
Acheulian in times of moderate temperature and retreating seas.
The
Amudian may occur at a time of cooler temperatures and marked sea re­
gression, though previous to the maximum cold periods evidenced in
later units.
Based on data available at present, it is difficult to
identify the specific activities associated with each of these facies,
mostly because of the reasons discussed in the previous chapter.
But
it is clear that the relationships between them are more subtle than
was originally anticipated.
31
Following the Mugharan industries are those which collectively
fall into a characteristic Levantine Mousterian pattern0 However,
while all of these units maintain a high emphasis on Levallois manu­
facture, there are significant differences between themu
These dif­
ferences will be discussed further in Chapter 4 0 The first Mousterian
industries, found in Unit X, are, in many senses, transitional between
the Mugharan and Mousterian<>
This transitional status is reflected by
a number of things, including a gradual increase in Levallois technique
with a concomitant decline in the number of bifaces, and by changes in
artifact shape (Jelinek 1980; Dibble and Chase 198l)o
So far there
have been no published accounts of similar industrieso
Unit
IX, roughly equivalent to Garrod1s Layer D, contains a
Lower Mousterian industry (Phase 1 Mousterian in Copeland’s 1975 termi­
nology), which has many counterparts throughout the Eastern Mediter­
ranean littoralo
Two of the defining characteristics of this industry
are the heavy emphasis on laminar Levallois flakes (with either bi- or
uni-directional preparation) and the relatively high percentage of
elongated Levallois points (thus Perrot’s 1968 designation of "Mousterien de Pointes Allonges”)o
It is relatively certain that this
Mousterian is associated with a marked sea retreat and relatively
cooler conditions (Jelinek et alo 1973; Farrand 1979)»
It is inter­
esting that the correspondence in climate between this Lower Mousterian
and the Amudian is matched by a similarity in industry, that is a high
percentage of true bladeso
Unit 1 (which corresponds to Copeland’s Phase 2 Mousterian)
shows more of an emphasis on radially prepared Levallois flakes with
32
a relative decrease in the frequency of Levallois points.
During this
time in the depositional history of the cave the chimney opened up
above the inner chamber, allowing for the washing in of terra rosa
clayey sediments from the overlying surface.
It also appears likely
that the site function changed considerably at this time (Jelinek
et al. 1973; in press).
Although there are perhaps seven distinct industries present
at the site, there is also clear evidence of continuity in technologi­
cal development,
Jelinek (1975; 19&0) has shown that in terms of at
least one variable, flake width relative to thickness, there is a unilineal trend that cross-cuts all of the industries.
This trend, shown
in Figure 1, appears also to hold true for other Lower and Middle paleo­
lithic assemblages in the Near East.
Moreover, given the typological
relationship noted above for the Acheulian and Yadrudian and the tran­
sitional nature of Unit X, there is no evidence to suggest that there
are major cultural breaks in the Tabun sequence, with the possible
exception to the Unit XIV-XIII succession.
Therefore, given the well-
controlled collection procedures, the materials recently excavated from
Tabun offer an excellent opportunity to examine technological continuity
and change in a restricted setting.
The present study utilizes data from each of the seven indus­
trial manifestations discussed above,
The Yabrudian, because it occurs
both early and late in the sequence, was sampled twice for a total of
eight data sets altogether.
For the most part (where sample sizes
permitted), each of these data sets represents materials from single
stratigraphic contexts.
It was felt that by limiting most of the more
33
UNIT
l-VIM
X
X
II
V
mean
variance
Figure 1.
i
2.0
5.0
4.0
3.0
I
3.0
i
4.0
I
5.0
Temporal change in mean and variance of width/thickness of
complete flakes from Tabun. — Mean = dots, solid line;
variance = crosses, dashed line. After Jelinek 1980.
34
detailed analyses to particular beds it would be possible to compare
only the extreme examples of each of the industries and avoid any
problems of mixture which might have occurred during the deposition
of an entire Unite
Moreover, this approach allowed for the collection
of data from virtually all of the relevant available material from
each bedo
We shall now turn our attention to a brief description of
each of the data set that will be used for analysis»
In this study, the "Layer G" (Unit XIV) Upper Acheulian is
represented primarily by Bed 90E1, augmented by a few specimens from
90E2o
From the collection obtained from both of these two levels, 716
lithic artifacts were recovered, of which a little over twenty-one per­
cent were retouched flake tools (see Table 2)„
percentage of bifaces and biface fragmentso
There is also a small
Figure 2 (see also Table 3)
shows a cumulative graph of the level following Bordes” (196lb) typology
(based on the essential count which excludes types 1 through 3 and 46
through 50)o
From this it is possible to see a characteristic
Acheulian pattern of moderate numbers of most types, though with a
relatively high percentage of naturally backed knives (type 38),
small but definite Levallois component is also presento
A
Table 4 pre­
sents some of Jelinek's unpublished data regarding general technique
observed on flakes and flake tools«
The Acheulian facies of the Mugharan Tradition is represented
in this study by bed 7611, with a few specimens drawn from bed 76128*
Looking at the inventory data presented in Table 3, this Acheulian
appears to have more bifaces and fewer retouched tools than in the
preceding bedso
In fact, if the retouched pieces alone are taken into
35
Table 2o
Basic inventory of Beds 90E1 and 90E2o
Artifact Class
N
Percent
Retouched tools
151
2101
Complete flakes
93
13°0
26?
37°3
3^
4<,7
135
l809
Broken flakes
Flake fragments
Cores
Bifaces
23
3=2
Biface fragments
13
lo8
4
6
Figure 2,
8
10
12
14
16
18
20
22
24
26
28
30 32
34 36 38
40 4 2
44
51
53 55
57
59
62
Cumulative graph of essential count of Mugharan Acheulian
and Unit XIV material from Tabun. — Mugharan Acheulian =
dashed line; Unit XIV = solid line.
VI
ON
37
Table 3
°
Type inventory for Beds 90E1 and 90E2»
Type
N
Type
9
8
33
13
10
17
34
1
11
4
35
1
13
1
36
1
18
1
38
41
19
3
4o
16
21
13
42
26
23
5
43
14
24
1
44
3
25
, 2
45
6
26
1
51
1
29
1
55
1
30
4
59
1
31
2
61
3
32
8
62
N
.
6
205
Table 4 0 Flake technique for Beds 90E1 and 90E2<,
N
Percent
291
93=3
Levallois
5
1=6
Bifacial retouch
8
2=6
Other
8
2=6
Technique
Normal
38
Table 5°
Basic inventory data for Beds 76X1 and 76X2B=
Artifact Class
N
Percent
Retouched tools
202
12o9
Complete flakes
170
10=9
Broken flakes
500
31=9
Flake fragments
144
9=2
Cores
243
15=5
Bifaces
217
13=9
90
5=7
Biface fragments
39
consideration, this Acheulian contains 60 percent bifaces and biface
fragmentso
In terms of basic flaking technique (Table 6 ), however,
there are no major differences*
In terms of typology (see again Fig* 2
sind Table 7) we see a typicsil Acheulian pattern, although with a fairly
high proportion of notches and denticulates*
The Yabrudian, which has two major occurrences in Tabun, is
represented in the present study by two distinct loci*
The older of
these (which will be referred to as ’’Lower'* Yabrudian) comes from beds
82BI and 82BS, while the younger (i0e 0 ’’Upper” Yabrudian) is derived
from bed 75SIo
Table 8 presents the basic inventory data for these
beds, and it is clear that there is a strong resemblance between the
two*
The characteristic Yabrudian pattern is quite noticeable from
this table in the extremely high percentage of retouched tools and the
low percentage of bifaces*
A look at the cumulative graph for these
levels (Fig 3 and Table 9) shows a strong resemblance to French Quina
Mousterian, as noted by Perrot (1968)*
In fact, other than scrapers
the only tool types present in any number are notches and denticulates*
As for basic flaking technique, Table 10 shows that there is nothing
very outstanding about these industries, although the percentage of
Levallois technique is higher in the Upper Yabrudian*
As was noted earlier, the Amudian comes from a restricted con­
text in the cave, specifically Bed 751°
The basic inventory of the
Amudian from Bed 7511 (Table 11) shows a relatively high percentage of
complete flakes and very few bifaces*
tools is moderate*
The percentage of retouched
In terms of technique (Table 12), there is a higher
percentage of Levallois than is found in the other Mugharan industries*
40
Table 60
Flaking technique in Beds 7611 and 751280
N
Percent
504
93.5
Levallois
12
2^2
Biface retouch
16
3=0
7
1=3
Technique
Normal
Other
Table 7=
Type
Type inventory for Beds 7611 and 76l2B0
N •
Type
N
5
1
27
1
9
11
28
2
10
35
30
1
11
5
31
2
13
6
32
7
14
1
33
4
15
3
37
1
17
2
38
82
18
2
40
10
19
6
42
20
20
1
43
34
21
10
45
18
23
14
59
2
24
1
61
18
25
5
62
25
26
3
333
41
Table 8e Basic inventory data for Beds 75SI ("Upper1* Yabrudian) and
82BS and 82BI ('•Lower" Yabrudian)0
Upper Yabrudian
N
Artifact Class
Percent
Lower Yabrudian
N
Artifact Class
Percent
Retouched tools
22?
40o0
Retouched tools
560
47 =5
Complete flakes
102
18=0
Complete flakes
124
10=5
Broken flakes
129
22=7
Broken flakes
297
22=2
Flake fragments
39
6=9
Flake fragments
23
2=0
Cores
51
9=0
Cores
147
12=5
Bifaces
16
2=8
Bifaces
19
1=6
4
=7
9
=8
Biface fragments
Biface flagments
4
6
Figure 3
8
10 12 14 16 18 20 22 24 26 28 30 32 34 36 *8 40 42 44 51 53 55 57 59
62
Cumulative graph of essential count of Upper Yabrudian
and Lower Yabrudian from Tabun. — Upper Yabrudian =
dashed line; Lower Yabrudian= solid line.
-p-
IX)
Table 9=
Type inventory for Beds 75S1 ("Upper" Yabrudian) and 82BS
and 82BI ("Lower" Yabrudian)0
Upper
Yabrudian
N
Lower
Yabrudian
N
Type
Upper
Yabrudian
N
Lower
Yabrudian
N
4
0
1
25
4
4
5
0
1
26
0
2
6
0
3
27
2
0
8
0
2
28
1
0
9
105
29
0
2
10
25
60
177
30
3
2
11
4
19
32
3
4
12
5
10
33
5
6
13
5
11
36
3
0
14
3
2
37
6
2
15
4
15
38
25
28
16
1
0
40
1
5
17
2
1
42
3
22
18
1
4
43
10
23
19
7
18
45
1
5
20
1
0
51
1
3
21
22'
34
51
53
0
1
3
15
60
0
1
23
24
59
61
1
6
24
0
1
62
14
0
262
611
Type
Total
44
Table 10=
Flaking technique for Beds 75S1 ("Upper” Yabrudian) and
82BS and 82BI ("Lower” Yabrudian)=
U p p e r Y a b r u d ia n
T e c h n iq u e
N
N o rm a l
L e v a llo is
B i f a c i a l R e to u c h
T a b le
11=
B a s ic
P e rc e n t
287
91.7
20
6=4
6
1=9
in v e n to r y
fo r
L o w e r Y a b r u d ia n
T e c h n iq u e
N
697
97=8
L e v a llo is
6
=8
B i f a c i a l R e to u c h
7
1=0
O th e r
3
=4
N o rm a l
B ed
P e rc e n t
7511.
N
P e rc e n t
R e to u c h e d t o o l s
216
29.6
C o m p le t e
198
27.1
208
28 =5
51
7.0
44
6=0
9
1.2
4
.5
A r tifa c t
B ro k e n
F la k e
C la s s
fla k e s
fla k e s
fra g m e n ts
C o re s
B ifa c e s
B ifa c e
T a b le
fra g m e n ts
12=
F la k e
t e c h n iq u e
f o r Bed
7511=
N
P e rc e n t
398
87.7
L e v a llo is .
39
8=6
O th e r
17
3.7
T e c h n iq u e
N o rm a l
45
which reflects the production of the Amudian prismatic blades= The
big difference, however, is in terms of typology, where we see in
Figure 4 and Table 13 a marked emphasis on Upper paleolithic types
(types 30 through 37)»
In addition, there are moderate percentages
of scrapers, including dejete and transverse forms.
Beds 711 and 72S provide this study with a sample of the Tran­
sitional Unit X materialo
Within these beds we see from Table 14 a
definite increase in complete flakes, which correlates with an in­
crease in Levallois technique (Table 15)°
There is, however, a strong
continuation of bifaces and a decrease of other retouched pieces.
The
cumulative graph of this industry (Fig, 5 and Table 16) shows that it
is fairly generalized.
In fact, in many ways this industry appears to
be typologically similar to the Mugharan Tradition Acheulian facies of
Bed 7611 except for slightly higher percentages of simple side scrapers.
For this study, Bed 66 was selected as representative of the
Layer D Lower Mousterian,
In terms of basic inventory (Table 17), Bed
66 has an even higher percentage of complete flakes than the Transi­
tional sample and very few bifaces.
lower than that of Unit X,
The retouched tool component is
Table 18 shows that for this bed
Levallois technique is extremely high, with almost 4y percent of the
observable flakes being Levallois,
As would be expected, there is a
high percentage of Levallois points (see Fig, 5 and Table 19),
At
th e
tim e
th is
m a t e r ia l h a d a lr e a d y
J e r u s a le m
U n it I
th u s
beds' in
s t u d y w a s u n d e r t a k e n , m uch o f t h e
been re tu rn e d
n e c e s s ita tin g
th e
th e
to
th e
R o c k e f e l l e r M useum i n
d r a w i n g o f s a m p le s
m a t e r i a l r e m a in in g
in
U n it
Tucson,
fro m
s e v e ra l
T h e re fo re ,
th e
I
4
6
Figure 4.
8
10
12
14
16
18
20
22 2
4 26
28 3 0 32
34 3 6
38 4 0 4 2 4 4
51
53
55 5 7 5 9
62
Cumulative granh of essentiel count of the Amudian from
Tabun.
-p-
CT\
4?
Table 13o
Type inventory for Bed 7511o
Type
N
Type
N
9
11
32
10
10
34
33
1
11
2
36
42
15
2
37
41
15
3
38
67
18
1
4o
2
19
3
42
6
21
14
43
5
22
1
45
1
23
16
51
1
25
1
54
1
26
2
59
1
27
1
61
2
30
2
62
15
Total
288
Table l4c Basic inventory of Beds 711 and 725o
N
Percent
Retouched tools
129
15=8
Complete flakes
183
22=5
Broken flakes
265
32=6
Flake fragments
78
9=6
Cores
90
11=1
Bifaces
46
5.7
Biface fragments
23
2=8
Artifact Class
48
Table 15o Flaking technique for Beds 711 and 72Se
Technique
N
Normal
294
73.9
Levallois
93
23.4
Bifacial retouch
10
2=5
1
o3
Other
Percent
X-
4
6
Fif^ure 5*
8
10
12
14
16
18
20
22 2 4
26
28
30
32 3 4
36 3 8
4 0 42
44
31
53
55
57
59
62
Cumulative paraph of essential count of the Upper Mousterian,
Lower Mousterian and Transitional Mousterian from Tabun. —
Upper Mousterian = alternating line; Lower Mousterian =
dashed line; Transitional Mousterian = solid line.
xO
50
Table 16=
Type inventory for Beds 711 and 728=
N
Type
N
4
1
29
1
5
2
32
1
7
3
33
1
9
21
36
1
28
37
3
11
1
38
36
12
1
40
3
15
4
42
9
17
2
43
14
21
3
45
7
22
3
55
1
23
12
61
2
25
7
62
12
26
1
Type
10 .
T a b le
17=
A r tifa c t
R e to u c h e d
C o m p le te
B ro k e n
F la k e
B a s ic
C la s s
660
N
P e rc e n t
67
17c 6
fla k e s
128
33 06
141
37=0
11
2=9
30
7=9
4
1=0
fra g m e n ts
B ifa c e s
f o r Bed
180
to o ls
fla k e s
C o re s
in v e n to r y
Total
51
Table l8„ Flaking technique for Bed 660
T e c h n iq u e
N
P e rc e n t
N o rm a l
139
52.9
L e v a llo is
123
46,8
1
,4
B ifa c e
T a b le
re to u c h
19=
Type
in v e n to r y
fo r Bed
66=
N
Type
N
4
4
31
2
6
1
32
3
7
5
33
1
9
6
34
1
10
12
35
11
3
37
5
12
1
38
14
13
1
40
2
15
3
42
4
19
1
43
3
21
1
45
3
25
1
54
1
29
1
62
5
Type
•
T o ta l
1
85
following data relate to the Unit as a whole„
In terms of basic in­
ventory (Table 20), Unit I shows a decrease in the percentage of
retouched tools, and a high increase in the percentage of broken and
fragmentary flakes as compared with the Bed 66 materialo
This is due,
above all, to the fact that the beds in Unit I were repeatedly burned
in prehistoric times (again probably relating to changes in site func­
tion) « Such activity resulted in a high occurrence of thermal fracture
of the lithic material0
The basic flaking technique (Table 21) still
maintains a high emphasis on Levallois, though not as high as Bed 66„
The typology differs from the Lower Mousterian in having lower per­
centage of Levallois points (408 percent here as compared with llo5
percent in Bed 66) and a higher percentage of naturally backed kniveso
The cumulative graph for the essential count is shown in Figure 5? with
the absolute figures presented in Table 22=
We will now proceed from this summary of the samples from Tabun
to focus on those aspects of technological variability that appear to
directly affect lithic variation in form0
z
53
Table 20c Basic inventory for Unit !»
Artifact Class
N
Percent
Retouched tools
20?
4.7
Complete flakes
1351
30=9
Broken flakes
1902
43=6
Flake fragments
651
14.9
Cores
255
5=5
Table 21=
Flake technique for Unit 1=
Technique
N
Percent
2151
71=8
813
27=1
8
=3
24
=8
Normal
Levallois
Biface retouch
Other
54
Table 22=
Type
Type inventory for Unit I
N
Type
N
5
5
29
1
6
1
31
2
7
1
32
5
9
19
33
6
10
48
35
2
11
8
36
1
12
2
37
5
15
3
38
202
14
4
39
5
15
5
40
8
17
1
4l
1
19
5
42
13
20
2
43
34
21
1
44
1
22
1
45
8
25
5
54
11
28
1
56
Total
406
CHAPTER 3
TECHNOLOGICAL FACTORS IN BASIC FLAKE PRODUCTION
The primary focus of this study is on technological variability
employed by the flintknapper and its relationship to variability in
observable attributes of lithic artifacts*
There are two major reasons
why technology should be examined in detail, besides the fact that it
is one of the four major contributors to lithic variability*
First, as
was discussed in Chapter 1, the effects of technology have been analyzed
through both replicative and controlled experiments*
On the basis of
the knowledge gained from these studies there is a high probability
that many of the specific effects of technological variation can be
isolated in prehistoric assemblages*
Second, as was also argued in the
first chapter, technology, as it operates on lithic formal variability,
often limits the potential range of functional or stylistic variability*
Before the effects of function or style are examined in lithic assem­
blages, therefore, it is best to control for the effects of technologi­
cal variability in a manner similar to that presented in Chapter 1*
As is discussed further in the next chapter, technological variation
reflects, in many ways, differences in strategies employed to produce
desired end-products*
55
The Evidence from Controlled Experiments
Before turning to the technological aspects of the Tabun collec­
tions, it is pertinent to review some of the findings that have been
obtained through controlled experiments» There have been many such
experiments focusing on technological factors (Bonnischen 1977; Faulkner
1972; Speth 1972, 1974, 1975)o However, there is one problem with the
approach taken by these investigators» Primarily this relates to the
fact that their experimental design emphasized the testing of principles
of fracture mechanics regarding material stresses and fracture ini­
tiation,.
Without doubt, an understanding of these physical relationships
is important in its own right, but it is also true that these phenomena
are not apparent to the flintknapper, who is instead interested in the
more obvious variables that he can understand and controlo
Referring
to a discussion presented in the Introduction, there are several levels
of phenomena to which the term technology applies0 The contrast pre­
sented here is between the level understood by the flintknapper, in
terms of his behavior, and the level of fracture mechanics.
For the
archaeologist interested in reconstructing f1intknapping strategies on
evidence available only from the by-products of the process, the knowl­
edge of relationships that exist between behavior (such as core prepara­
tion, patterns of extraction, etc,), and the resulting flake morphology
are, at present, more relevant than an understanding of the physical
mechanics that are ultimately responsible for the behavior of the stone
itselfo
57
Recently, a colleague (John Whittaker) and I performed a set of
controlled experiments that emphasized relationships that could be
observed on lithic artifactso
The method used in our experiment (see
Dibble and Whittaker in press) most closely resembled that used by
Speth, except with respect to the form of the glass cores*
Our approach
was to manufacture cores from half-inch plate glass and remove flakes
from the edge rather than the flat surface of the glass (cf*, Faulkner
1972)o The flakes thus produced were therefore of a constant width
and most closely resembled burin spalls*
This design allowed for the
production of cores with a wide and continuous range of exterior plat­
form angles, an attribute not varied in previous experiments*
Flakes
were removed by dropping steel balls of three different sizes and
weights from a constant height (see Fig* 6)*
The overall design of the experimental apparatus allowed for
the controlled variation and later analysis of several variables rele­
vant to lithic manufacture*
In this experiment, exterior platform
angle, force, angle of blow, and platform thickness represent inde­
pendent variables*
The dependent variables are length, thickness,
interior platform angle, and flake termination (for definitions of
these and other variables discussed in the text, see Appendix I)*
At this point there are a number of issues concerning our
analyses that should be discussed*
First among these is the distinc­
tion between independent and dependent variables*
As is true in any
scientific endeavor, the study of lithic production proceeds on the
assumption that not all observed variation is random, but instead
that some aspects of it are the result of one variable or two or more
58
A N G L E OF
B LO W
Figure 6.
Design of controlled experiment. — (a) Schematic drawing
of apparatus used in the controlled experiment of Dibble
and Whittaker. The gunsight was used in positioning the
glass core directly beneath the electromagnet, (b) Drawing
of a glass core depicting the manner in which it is struck.
After Dibble and Whittaker in press.
59
v a r ia b le s
a c tin g
c o v e ry o f
th o s e
th e
to g e th e r ,,
v a r ia b le s
b e h a v io r o f o th e r
d ir e c tly
e ffe c ts
a re
a re
c a lle d
c a lle d
T h is
tio n s h ip s
th a t a re
v a r ia b le s .
is
e x is t
in
o f e x te r io r
th e
fo r
d e c i d i n g w h ic h v a r i a b l e s
fo rc e
c o n te x t
p la tf o r m
an a c tu a l
a re
of
th e
th o s e
m in e d b y t h e s e
th e n ,
r e s p o n s ib le
v a ria b le s
fla k e
b lo w ,
is
fo r
th e
and th o s e
th a t
d is ­
a ffe c tin g
w h ic h a f f e c t
o th e rs
e x h ib it
th e
of
fla k e
and te r m in a tio n
a re
th o s e
re m o v e d .
c o re
e tc ,,
d ir e c tly ,
but
in d ir e c tly
a re
p ro d u c tio n ;
on fla k e
le n g th .
a re
o f th e
th e
e x a m p le ,
The r a tio n a le
a re
dependent is
a re
c o n t r o lle d
Thus,
a ll
a s p e c ts
p la tf o r m
r e s u ltin g
Thus,
p re p a r a tio n ,
th a t
a ttr ib u te s
b y th e
e ffe c ts
fla k e s
Dependent
a re
d e te r­
such as
flin tk n a p p e r
o f th e
b y th e
o f c o re
in d e p e n d e n t v a r i a b l e s .
c o n t r o lle d
th ro u g h
fo r
th a t
m o r p h o lo g y ,
in d e p e n d e n t v a r i a b l e s .
d im e n s i o n
in d e p e n d e n t-d e p e n d e n t r e l a ­
i n d e p e n d e n t a n d w h ic h
is
a ttr ib u te s
th o s e
a n g le
a re
such as e x t e r io r
a n d a n g le
v a r ia b le s
Those
in d e p e n d e n t v a r i a b l e s
k n a p p e r b e fo re
p re p a r a tio n ,
d ir e c tly
c o n c e rn e d w it h
e ffe c t
fo llo w s :
m a jo r g o a l s ,
in d e p e n d e n t v a r i a b l e s ,
th e
as
th e
dependent v a r ia b le s .
s tu d y
th a t
O ne o f
fla k e
not
in d e p e n d e n t
v a r ia b le s .
G iv e n
th is
d is tin c tio n
O ne i m p o r t a n t c o n s i d e r a t i o n
’’ in d e p e n d e n t"
s h ip
at
r e la tio n s h ip s
a ff e c tin g
e x a m p le ,
th a t
e x te r io r
be
sh ow n t h a t
w ill
a ls o
by o th e r
is
o r " d e p e n d e n t"
b e in g a d d re s s e d
a c tio n s ,
th e
th e re
th a t
is
la b e lin g
In
th is
d im e n s io n s .
p la tfo r m
a n g le
e x te r io r
p a r tic u la r ly
th e
p o te n tia l
s tu d y
It
a ffe c ts
p la tfo r m
p la tfo r m
s o u rc e s
p a r tic u la r
th e
fo c u s
w i l l be
fla k e
a n g le
o f c o n fu s io n .
o f a v a r ia b le
d e te r m in e d b y th e
tim e ,
fla k e
a re
is ,
fa c e ttin g .
is
show n,
as
r e la tio n ­
on
fo r
le n g th .
But i t
in
tu rn ,
a ffe c te d
Is
e x te r io r
6o
platform angle then a dependent or independent variable?
It is depen­
dent as far as the relationship between it and facetting is concerned:,
But with respect to its relationship to flake length it is an inde­
pendent variableo
In the determination of length it does not matter
how the exterior platform angle was produced:
given that angle, a
flake of a certain length can be expectedo
- Another point concerns the statistical methods used in these
analyseSo
The goal of this study is to isolate independent-dependent
relationships such as those just discussedo
Thus there is a heavy
reliance on correlation and regression analysis0 For our purposes it
is useful to make a distinction between these two methods (see Snedecor
and Cochran 196?; Beals 1972)0
Correlation analysis is used to summarize the relationship
between one dependent variable and one or more independent variableso
One statistic computed in the course of this kind of analysis is the
correlation coefficient, _r, which is a measure of the degree of close­
ness between the dependent and independent variables<>
This coefficient
always takes on a value between 1=0 and -lo0, where the sign indicates
the type of relationship (positive vs0 inverse) and the absolute value
is a measure of the strength of the relationship (a value of lo0 indi­
cates perfect correlation)0 Another measure, R-square, represents the
proportion of variance in the dependent variable that is explained by
the independent variablec
Regression analysis, on the other hand, is used for purposes of
predicting the value of the dependent variable given certain values for
61
the independent variables«, Basically, regression analysis computes the
line which best fits the observed data.
Its mathematical form is;
Y = a + bX + e
where Y is the predicted value of the dependent variable, X is the value
of the independent variable, parameter a is the mean of the population
corresponding to X=0, parameter b is the slope of the regression line,
and e is the part of Y unexplained by (i.e., independent of) X.
Correlation and regression analysis are, of course, two sides
of the same coin and are most often used simultaneously.
However, the
distinction between them is drawn here because of the emphasis, and to
a large extent the limitations of, the present study.
The purpose here
is to discover interpretable relationships between the independent
variables controlled by the knapper and the dependent variables observ­
able on the resulting flakes.
The most useful statistics in this regard
are r and R-square because they reflect the strength of association
between the variables.
The parameters computed on the basis of regres­
sion analysis, although presented throughout this dissertation (in both
standardized and raw form) are not as useful.
This is because the
particular relationships’between the variables that are expressed by
the parameters a and b change with the addition of other independent
variables.
These other variables, such as raw material, exterior core
morphology, etc., are not yet quantifiable in any meaningfully con­
tinuous fashion and so are not included in the analyses.
Nonetheless,
their addition would affect, in some unknown fashion, the relationships
expressed by the parameters of the regression equation.
On the other
62
hand,
th e
la tio n
a d d itio n
c o e f f i c i e n t w o u ld
O ne
a re
f i n a l p o in t
p re s e n te d .
a tio n s
s id e r e d
as
Thus,
w ill
I
a n a ly s is
do,
in
th e
is
c o n tr o lle d
r e s u lt s
not y e t
fin a l
c o r r e la tio n
th e re
as to
a re
n o t w ith
th e
b e t w e e n th e m
o f th e
r o le
p r in t,
of
lith ic
th e
e x p e r im e n t c o n c e rn e d
a rg u m e n ts ,
v ir tu a lly
in te r io r
c o r r e la tio n
w ith
a ll
m anner i n
(s e e
and th e
s u p p o r t e d b y my own
appear
in
m in d i t
p la tfo r m
th is
s h ip w as n o t v e r y h ig h
s h o u ld be c o n ­
in
th ro u g h
is
o th e rs 0
c o r r e la tio n
w h ic h
th e
4),
fa c to rs
m ost im p o r t a n t
s im p ly w i t h
fla k e
m o r p h o lo g y .
v a r ia b le ,
(s e e F i g ,
a lt h o u g h
7)=
c r u c ia l
th a t
fin d in g
s in g le e x h i b i t e d
F la k e
to
a ffe c t
p o in t
th e
B ecause
an u n d e r­
fla k e
b r ie fly
o f th is
fo r m
h e re .
c o n tr o lle d
p la tfo r m
a n g le
dependent v a r ia b le s .
a s ig n ific a n t
th e
tu rn
and W h itta k e r h ave
p re s e n te d
th e
th is
to
in d e p e n d e n t v a r i a b l e s
o f e x te r io r
of
At
but
th e y a re
th e y a re
v a lu e s
at
now p o s s i b l e
e x p e r im e n t .
r e s u ltin g
and because
th e
s u m m a r iz e s a s s o c i ­
v a r ia b le s
th a t
C h a p te r
d o m in a n t r o l e
of
a c t u a l a n a ly s e s
c a u s in g v a r i a t i o n
c o n tr o lle d
a s s e m b la g e s ,
th e
th e
flin tk n a p p e r .
te c h n o lo g ic a l
s in g le
c o rre ­
about c a u s e -a n d -e ffe c t.
e x p e r im e n t p e r fo r m e d b y D ib b le
o f th e
P e rh a p s
th e
c o n s id e r a tio n s
th ro u g h
th e
c a u s e -a n d -e ffe c t r e la tio n s h ip s ,
by
o b t a in e d
of
s ta tis tic ..
a n a ly s is
why c e r t a i n
a s s o c ia tio n s
b y th e k n a p p e r
p r e h is to r ic
e x a m p le ,
th e
re p re s e n t
above
in
a ffe c tin g
s tre n g th e n
and s a y s n o th in g
c o n t r o lle d
a p p e a re d
s ta n d in g
c o m p u ta tio n
th a t
above,
fa c t,
le v e l
r e la tio n s h ip s
in
tru e
e x p e r ie n c e ,
r e s u lts
o u r c o n c e rn
th e
th e
s h o u ld b e b r o u g h t o u t b e f o r e
suggest th a t
on th e
th e
in
i n d e p e n d e n t a n d b e v ie w e d a s
W ith
a re
is
a s d is c u s s e d
flin tk n a p p in g
to
It
v a r ia b le s
o n ly
b e tw e e n v a r i a b l e s
H o w e v e r,
le a s t
o f th e s e
s tre n g th
of
te r m in a tio n
in
For
n e g a t iv e
th e
r e la tio n ­
( T a b le
23)
was
63
ANGLE
135 '
130
e•
PLATFORM
••
••
• ••
25
INTERIOR
• •• •
•••
••
120
N = 178
r = -.3 9 2
.154
30
40
EXTERIOR
Figure 7.
50
PLATFORM
60
70
80
90
ANGLE
Scatter diagram of relationship of Interior Platform Angle
with Exterior Platform Angle for flakes produced in con­
trolled experiment. — Both angle measurements are in
degrees. After Dibble and Whittaker in press.
64
Table 23=
Exterior platform angle by categories of flake termination
in controlled experiment.
Exterior Platform Angle
S.D.
Termination
Mean
Feather
41.8
9=8
26
Hinge
61.5
14.0
220
Overshot
76 =7
9=4
27
N
(Dibble and Whittaker in press)
All comparisons between termination types significant to O01 level
through t-tests and assuming unequal variances.
65
a ls o
a ffe c te d
la tte r
te n d e d
" n o r m a l"
to
r e s u lt
fe a th e r
W h itta k e r
th e
by e x t e r io r
in
in
in
th is
th e
a n g le
m o re h i n g e d
te r m in a tio n )0
p re s s ),
c o re s used
p la tfo r m
is
As i s
in
or
t h a t h ig h e r v a lu e s
o v e rs h o t
a rg u e d
m ost p r o b a b ly
in
o f th e
fla k e s
(v e rs u s
th e
our paper
(D ib b le
and
a r e s u lt
of
th e
g e o m e try o f
e x p e r im e n t0
F o r th e lo w e s t e x t e r i o r p la t f o r m a n g le s , th e i n t e r i o r and
e x t e r i o r s u r fa c e s o f th e f la k e te n d to c o n v e rg e and th e f la k e
t e r m i n a t e s a t t h e i n t e r s e c t i o n o f t h e s e tw o s u r f a c e s i n a
r e g u la r fa s h io n .
F o r m id d le r a n g e s o f th e e x t e r i o r p la t f o r m
a n g le , th e s e s u r fa c e s a r e e s s e n t i a l l y p a r a l l e l , and f o r th e
h ig h v a lu e s o f e x t e r i o r p la t f o r m a n g le , th e y d iv e r g e .
In
e i t h e r o f t h e l a t t e r tw o i n s t a n c e s , t h e f l a k e t e n d s t o t e r m i ­
n a t e i n a h in g e f r a c t u r e = A t th e h ig h e s t e x t e r i o r p la t f o r m
a n g l e s , t h e f l a k e s c a n o v e r s h o o t o r f a i l t o d e v e l o p com­
p l e t e l y , p e rh a p s as a fu n c tio n o f f o r c e .
^ C o m p a re t h e o v e r ­
s h o t f l a k e s p ro d u c e d b y F a u lk n e r (1 9 7 2 ) u s in g a c o n s t a n t
e x t e r i o r p l a t f o r m a n g l e o f 9 0 d e g r e e e£7 . . . .
I n o r d in a r y
k n a p p i n g s i t u a t i o n s i t i s p r o b a b l e t h a t e x t e r i o r c o r e m o r­
p h o lo g y p la y s a n im p o r t a n t r o l e i n d e t e r m in in g t h e t e r m i ­
n a tio n o f f la k e s .
I n p a r t i c u l a r , a c o re w ith a co n vex
f l a k i n g s u r f a c e w i l l b e m o re l i k e l y t o p r o d u c e f l a k e s w i t h
f e a t h e r t e r m in a t io n s b e c a u s e o f t h e g e o m e tric re a s o n s g iv e n
above.
The
d im e n s io n a l a t t r i b u t e s
d e p e n d e n t on th e
fo rc e
For
and p la tfo r m
th e
fo r m
m o m e n t,
a n g le
by e x te r io r
le t
th e
and
9
p la tfo r m
it
a re
c o n s ta n t.
c le a r
a n g le
a re
th ic k n e s s
fo r
10
show s,
le n g th
th is
a n g le
in
th a t
a n a ly z e d
le n g th
a ll
th ic k n e s s
fo r
is
a
is
c o m p le x .
and e x t e r i o r
c o n s ta n t
p la t­
fo rc e .
o n ly m in im a lly a f f e c t e d
b y p la tfo r m
s in g ly .
a re
c o n ju n c tio n w it h
r e la tio n s h ip
b e e x a m in e d
th e s e
and
b e tw e e n l e n g t h
and n o t a t
c l e a r e r w hen o ne o f
F ig u r e
H o w e v e r,
th ic k n e s s
is
fla k e
p la tf o r m
r e la tio n s h ip
in d e p e n d e n t v a r i a b l e s
s h ip s
fo rm
8
o f e x te r io r
th ic k n e s s .
and p la tfo r m
F ro m F i g u r e s
th e
v a lu e s
of
t h ic k n e s s w hen
H o w e v e r,
in d e p e n d e n t v a r i a b l e s
fo r
e x a m p le ,
th e
e ffe c t
a p a r tic u la r
in te r v a l
o f e x te r io r
th e
is
on le n g t h
p la tfo r m
r e la tio n ­
h e ld
by p la t ­
a n g le .
I0.2
&3
LENGTH
8.4
N= 199
7.5 <
r = .72 9 4
6.6 '
R2= . 5 3 2 0
• •
5.7 <
•• •
• •
4.8 •
••
•
•
e
3.9
•
#
•
3.0
•
•
.
• •
•
•
•
•
•
e •
••
* e
• •
e
•
•
•
•
•
:
•
•
*
*
# •• • •
.
•
#
2.1
•e
1.2
•
33
39
44
50
56
EXTERIOR
Figure 8.
62
PLATFORM
67
73
79
84
90
ANGLE
Scatter diagram of relationship of length (in centimeters) with Exterior
Platform Angle (in degrees) for flakes produced in controlled experiment.
— After Dibble and Whittaker in press.
o\
I0.2 1
9.3 '
8.4 *
•
•
7.5
6.6
•
LENGTH
•
5.7
•
•
•
•
•
4.8
#
e
•
e •
e
• e
e
ee •
«
# # # • • • •
• •
e e e
•
*
e *
e
e e
•
•*.
# e
3.9
e
e
e
e
e
e
3.0
e e
e
2.1
e
e
ee
ee
e
'
e
*
*
e
e
e
e e
ee
e e e# e
e
e e
ee
*
e
e
e•
*
e
e
e
e#* e
e
e eee
e
ee
ee eee
•
e
e e e
e e
e e e
e
e
e e e
«
e •
N= 199
r = .0138
rV o o o z
e
1.2
.13
.28
.43
.58
.74
PLATFORM
Figure 9«
.89
1.04
1.19
1.34
1.49
THICKNESS
Scatter diagram of relationship of length with Platform Thickness (in
centimeters) for flakes produced in controlled experiment. — After
Dibble and Whittaker in press.
(JN
< 1
8 i
7
6
'
••
••
•
••
••
•
e •
EXTERIOR
••
PLATFORM
ANGLE ■ 45°-50°
N = 25
r = .939
R-
.3
.6
.9
PLATFORM
Figure 10.
1.2
.882
1.5
1.8
2.1
THICKNESS
Scatter diagram of relationship of length with Platform Thickness
(in centimeters) for one interval of Exterior Platform Angle for
flakes produced in controlled experiment. — After Dibble and
Whittaker in press.
Likewise„ Figure 11 presents data on the relationship between length
and exterior platform angle for one interval of platform thickness0 In
both cases, there is a high positive correlation between each inde­
pendent variable and lengtho
The question then arises as to why such
relationships break down when examined over the entire range of the
other independent variable <,
The reason is simply that variability in length (for a given
force) must be explained on the basis of exterior platform angle and
platform thickness acting together0 By performing a multiple regres­
sion in order to best express the relationship, we find that the
correlation coefficient between length and the two independent variables
taken simultaneously jumps to o799 (Table 24 and Fig0 12)0 To an even
greater extent flake thickness is seen to be a function of these plat­
form characteristics for a given ball size with a computed multiple r
value of o908 (Table 25 and Figo 13)o
However, for a given force, the relationship of exterior plat­
form angle and platform thickness to the dimensional attributes of the
flakes is still more complex than the linear model obtained through the
multiple regression*
In the first place, there is a decrease in the
percentage of variation of the dimensional attributes explained by
values of platform thickness as exterior platform angle is increased*
This is expressed in Table 26 by a decrease in the R-square values
computed on platform thickness and length for each increasing interval
of exterior platform angle*
I n .other words, as exterior platform angle
increases, length increases but is less predictable for a given value
of platform thickness*
8.8
PLATFORM THICKNESS = 45-50°
N = 19
7.7
r = .964
6.6
R*= .929
•
LENGTH
5.5
4.4
••
*•
3.3
2.M
.
' .
#
"
I.I
36
42
48
EXTERIOR
Figure 11.
54
60
PLATFORM
66
72
78
84
90
ANGLE
Scatter diagram of relationship of length (in centimeters) with Exterior
Platform Angle (in degrees) for one interval of Platform Thickness for flakes
produced in controlled experiment. — After Dibble and Whittaker in press.
3
\
Multiple regression for length with exterior platform angle
(EPA) and platform thickness (PT) for flakes produced in
controlled experiment <>
Multiple r
Length
df
280.716
158.470
195
197
140=358
Standardized
Beta
.0797
.00428
.869
.300
=355
F
345=33
57.55
Significance
V V
B
(Dibble and Whittaker in press)
172=71
.812
Standard
Error
B
2o28
F
00
EPA
PT
Analysis of Variance
Sum Squares
Mean Square
2
regression
residual
total
Variable
R-square = 0638
3
<1
Table 24„
II
71
7
6
5
LENGTH
• e
4
••
••
• •• •
••
• #
3
•
••
•• • •••
2
•• •
• ••
• ••
••
••
•• •
1.0
1.6
34
2.2
E S T IM A T E D
Figure 12.
4.0
4.6
5.0
5.6
LENGTH
Scatter diagram of length to estimated length (based on exterior platform
angle and platform thickness) in controlled experiment. — See Table 24.
After Dibble and Whittaker in press.
73
.=
o908
R-square = 826
Thickness
df
regression
residual
total
195
197
Variable
EPA
PT
Analysi;s of Variance
Sum Squares
Mean Square
2
24086
5-25
B
Standard
Error
B
-0235
0OOO8
08II8
-0547
461.64
12.43
=03
Standardized
Beta
.9827
.4826
F
F
912.95
220.16
Signifi­
cance
O O
H H
Multiple r
Multiple regression for thickness with exterior platform
angle (EPA) and platform thickness (PT) for flakes produced
in controlled experiment0
0A A0
Table 25»
(Dibble and Whittaker in press)
/'
#*/
• • **********
.6
►••• ******
«
*
*
•• ••Wt&Vw** .
• #*** ••*••*•• ••••
.3- *
•
* * * *
* *****
■»
»
»
i
»
'»
'■ »
'V
*
.2
.4
.6
.8
1.0
1.2
1.4
1.6
1.8
ESTIM ATED
THICKNESS
Figure 13 • Scatter diagram of thickness to estimated thickness (based on exterior
platform angle and platform thickness)in controlled experiment. —
See Table 25. After Dibble and Whittaker in press.
75
Table 26=
Mean length and median platform thickness and R-squares
between length and platform thickness (r) by intervals of
exterior platform angle for flakes produced with constant
force in controlled experiment.
E x te r io r
P l a t f o r m A n g le
M ean
L e n g th
M e d ia n
P la t f o r m T h ic k n e s s
R.S q u a r e
N
40-45
, 3.54
-79
-803
19
45-50
3.44
-70
OJ
00
000
25
50-55
3-44
067
0863
14
55-60
3-80
.71
.663
18
60-65
4.54
00
IA
.299
16
65-70
4,90
.63
=24?
21
70-75
5-68
-66
.194
9
75-80
5-45
=60
-126
22
80-85
5-87
-47
-024
26
( D ib b le
and W h itta k e r
in
p re s s )
76
It is difficult to explain why the strength of the relationship
between length and platform thickness decreases as exterior platform
angle increases.
Perhaps it is due to small and uncontrolled variations
in the platform or exterior surfaces of the core, But if so, such
variation would have been present to the same degree throughout the
range of exterior platform angles.
Therefore it would be possible to
conclude that the effect of these small variations increases as the
exterior platform angle increases.
But whatever the reason, the de­
creasing predictability of length to platform thickness means that the
correlation coefficient obtained through multiple regression represents
a sort of average correlation throughout the range of exterior platform
angle.
Another interesting effect that occurs as the exterior platform
angle is increased is that the values of platform thickness that result
in a flake decrease (see again Table 26),
In other words, the range
of possible platform thicknesses is reduced or limited as exterior
platform angle increases.
What this means is that increasing the
exterior platform angle will result in a larger flake, but to obtain
this flake one must use a smaller platform thickness.
Therefore, in
order to maximize flake length with a given force, it is necessary to
increase the exterior platform angle while limiting the platform thick­
ness to a smaller value.
Impact force, or in this case ball size, is an obvious inde­
pendent variable affecting these flake dimensions.
Table 2? shows mean
lengths and thicknesses of flakes produced by different ball size.
These findings are in essential agreement with those of Speth (1972,
77
Table 27°
Flake length and thickness (in centimeters) for three ball
sizeSo
Length
Mean
S oD©
Thickness
Mean
S=Do
1
2°8
°75
2=84
=75
48
2
3°4
loOO
3=42
1=04
65
4=4
1=50
4=39
1=49
199
Ball
3
'
(Dibble and Whittaker in press)
Ball Is lo25
Ball 2s lo6
Ball 3: 1°9
cm, 8*62 gm
cm, l6o35 gm
cm, 28017 gm
N
78
1975 ) w ho fo u n d t h a t f l a k e
p in g
a g iv e n
b a ll
fro m
T o s u m m a r iz e
e x te r io r
o f th e
p la tfo r m
le n g th
by e x te r io r
tio n ,
to
th e
a n g le
F la k e
le n g th
p la tfo r m
th ic k n e s s
c re a s e d
as e x te r io r
fin d in g s
of
is
la r g e
a n g le ,
m a k in g
th e s e
in d u s tr ia l
e x is t
to
fo rc e ,
p la tf o r m
sam e i s
a n g le
c o m p a r is o n s ,
in d e p e n d e n tly
fo llo w in g
te s ts
e x c e p tio n
to
b y in d u s tr y .
cases
w ith .
in
th e
d e a lin g w ith
a re
c le a r
s in c e
tru e
s iz e s
th a t
fo r
th e
th e
th e
e ffe c ts
to
fo r
to
th e
such as
not
n e c e s s a ry
a lw a y s
r e la tio n s h ip s
of
th e
v a r ia b le s
u n d e r c o n t r o lle d
w ith
a ffe c te d
th e
th e
th a t
to
b e in g
o n ly
te r m in a ­
a ls o
by
fo rm e r
de­
a re
g iv e n
th e re
it
a re
is o la tio n
c o n d itio n s .
For
fro m T a b u n ,
c o n tro l
In
fo r
d a ta .
m ost o f th e
T h e one
m a jo r
d ep en d on th e
v a r ia b le s
in
r e s u lts
e x a m in e d s h o u ld
a b re a k d o w n o f t h e
p a r tic u la r
th e s e
T h e re fo re ,
a v a ila b le
c o m p a r is o n s ,
a n a c t u a l a s s e m b la g e
in te r fe r e
th e
an y one a n a ly s is
th e s e
a n g le , w h ile
fla k e
w hat e x te n t
a s s e m b la g e
a ll
e x h ib it
of
a ll
Tabun M a te r ia ls
d e te r m in e
is
fo r
v ir tu a lly
a ffe c te d
ty p o lo g ic a l v a r i a b i l i t y .
p r e s e n tin g
c o u ld p o t e n t i a l l y
a ls o
th a t
in c r e a s e d .
a p p ro a c h p r e s e n ts
s a m p le
D e fin itio n s
it
a p p lie d
S a m p le
B e fo re
in
of
a re
th is
to
w ith
w as s i g n i f i c a n t l y
a lt h o u g h
a p r e h is to r ic
a ffilia tio n
by d ro p ­
we f o u n d
p la tf o r m
a n d t h ic k n e s s , h o w e v e r, w e re
and
a ffe c te d
e x p e r im e n t,
In te r io r
d e g re e ,
The
now n e c e s s a r y
ca n be a p p lie d
th is
o b s e rv e d .
C o m p a r is o n s w i t h
It
w e re
show ed s t r o n g r e l a t i o n s h i p s
a v e ry
p la tfo r m
th ic k n e s s
d i f f e r e n t h e ig h ts o
dependent v a r ia b le s
n o t e x p la in e d
and
fin d in g s
num ber o f
b e in g
d e a lt
A p p e n d ix I ,
s h o u ld
b e m e n t io n e d
a num ber o f
fa c to rs
o f r e la tio n s h ip s
in s ta n c e ,
th a t
th a t
th a t
in d e p e n d e n t
79
variables such as force or angle of blow cannot yet be calculated from
existing flakes.,
Also, there is no doubt that variables of the exterior
core morphology and differences in the materials play a crucial role in
affecting flake characteristics, but these cannot always be adequately
controlled,.
Therefore, it can be expected that the strengths of the
relationships that can be demonstrated would be somewhat less than
those obtained under controlled conditions..
Taking each of the dependent variables in turn, and beginning
with the relationship between exterior and interior platform angle, we
can see from Figure 14 that this relationship in the Tabun sample is
similar (difference between r ’s = 1 o3452, P = ol8) to that observed in
the experimental flakeSo
In both cases there is an inverse relation­
ship between these variables, although not very strong, especially for
the middle ranges of the variables.
This suggests that the interior
platform angle is simply a weak reflection of the exterior platform
angle.
For flake termination, the results obtained from the Tabun
material do not match those obtained in the controlled experiment as
closely.
Table 28 presents the data relevant to the relationship be­
tween exterior platform angle and flake termination; the only agreement
between these data and those from the controlled experiment is that
overshot flakes tend to have higher exterior platform angles.
Unlike
the results of the controlled experiment, hinged flakes tend to have
the same or even slightly lower exterior platform angles than do feather
terminations.
BO
iso
142
INTERIOR
PLATFORM
ANGLE
l»4
lit
III
103
ee
N" 355
r ■ -.4 9 1
to
R * .241
35
41
46
54
61
EXTERIOR
Figure 14.
67
PLATFORM
73
80
66
t3
ANGLE
Scatter diagram of relationship of Interior Platform
Angle with Exterior Platform Angle (both measurements
in degrees) for sample of flakes from Tabun.
99
81
Table 28»
Exterior platform angle by categories of flake termination
for samples from Tabun*
Termination
Mean
Exterior Platform Angle
S ©Do
Feather
76=2
10=4
356
Hinge
74=8
12=5
78
Overshot
79.6
10=5
56
N
82
H o w e v e r,
th e
d a ta
tr o lle d
b ia s e d
in
re tro s p e c t,
show o t h e r w i s e «,
g e o m e try
th e
e x p e r im e n t a l c o re s
th e
o n ly
e x te r io r
a n g le o
chance
s u rfa c e s
Thus,
b ilitie s
of a
fo r
th e
a ll
a la r g e
to
used
to
in
fro m
th e
(io e,,
s u r p r is in g
th e
r e s u lts
to
have
o f th e
e x p e r im e n t0
fla t)
con­
B ecause
e x te r io r
w as w hen t h e
p la tfo r m
th e
be
w e re p r o b a b ly h ig h ly
a r e la tiv e ly
e x te r io r
e x it
fa c t
te r m in a tio n
te r m in a tio n
due
in
e a r lie r ,
had s t r a ig h t
fe a th e r
fla k e
fla k e
o f th e c o re s
c o n v e rg e d
g iv e n
w o u ld
As w a s a r g u e d
e x p e r im e n t r e g a r d in g
b y th e
it
s u rfa c e s ,
in te r io r
and
s m a ll e x t e r io r
a n g le ,
p la tfo r m
th e
o n ly
h in g e
or
o v e rs h o o t
o th e r h a n d ,
it
is
c o re w as t o
p o s s i­
c o m p le te ly o
In
fo r
th e
le a s t
tio n
a c t u a l k n a p p in g
knapper
to
c o n tro l
some e x t e n t =
so t h a t
a llo w in g
to
fo r
th e
a
fe a th e r
a n g le o
c o re
p r e p a r a tio n *
th e
L e v a llo is
s u rfa c e
te c h n iq u e
can o c c u r w ith
th e s e
fo r
fe re n t*
In
p r o b a b ly
depends
w ith
th is
r e la tiv e ly
fe a th e r
case,
to
The n e x t s e t
re p r e s e n tin g
w id th ,
w ith
and
th e
th e
in v o lv e s
th e
in
is
h ig h e r
an d h in g e
th e
s p ite
fo rc e
e x te r io r
e x te n t
r e s u ltin g
is
p o in t
c o re
o f th is
is
c le a r
p la tfo r m
w ill
on th e
in
am ount o f
at
p re p a ra ­
som ew hat c o n v e x ,
o f a h ig h e r
it
p o s s ib le
te r m in a te s ,
e x te r io r
th u s
p la t­
k in d
o f e x te r io r
th a t
fe a th e r
a n g le s
and
th u s
n o t be v e r y
o f one t e r m in a t i o n
d if­
o r a n o th e r
fo rc e
a p p lie d ,
a h in g e *
o f dependent v a r ia b le s
A t th is
fla k e
c a re fu l
te r m in a tio n s
d im e n s io n a l a t t r i b u t e s
th ic k n e s s *
c o re
a n e x a m p le
p r o d u c tio n
a la r g e r
le s s
of
w h ic h a
such p r e p a r a tio n ,
te r m in a tio n s
a n g le s
th is
te r m in a tio n
G iv e n
on th e
m anner in
P r im a r ily ,
e x te r io r
fo r m
s itu a tio n s ,
to
o f th e
b e e x a m in e d a r e
fla k e s ,
c o m p a r is o n s o f
e x p e r i m e n t a l m a t e r i a l b e c o m e m uch m o re
th e
i*e*,
th o s e
le n g th ,
a r c h a e o lo g ic a l
d iffic u lt*
Two r e a s o n s
fo r
th is
fo r
th e
w e re
im p a c t f o r c e
c o n t r o lle d
d a ta
b r ie fly
th a t
fo rc e
th e
a re
r e s u lt
e x p e c te d
is
th e
s iz e .
of
s ta te d
w ill
is
im p o s s ib le
d e te r m in e d
c o n tr ib u to r
r e g a r d le s s
(a n d
above,
th e re
is
a b la d e
te n d
to
p re p a re d L e v a llo is
a ls o
c o re ,
y ie ld
c o re ,
fr o m
to
th e
in
th e
e x p e r im e n ta l
d im e n s io n s ,.
o f in d u s tr ia l
a re
c o n tro l
a s w as done
fla k e
unknow n)
to
a ffilia tio n ,
fo rc e s
th e y w i l l
be
o r u n e x p la in e d
v a r ia b ility .
r e la tiv e ly
c o n t r o ls b n
fe w
u n d o u b te d ly a
w ith
lo n g e r
fa c to r
a ffe c tin g
lo n g p a r a l l e l r id g e s
and n a r r o w e r
r e g a r d le s s
o f p la tf o r m
fla k e s
a lo n g
th a n
a
p r e p a r a tio n
fo rc e .
d a ta
a re
a ls o
tw o v a r i a b l e s
(th e y
w e re
h e ld
These v a r ia b le s
because
it
th is
nesso
is
d iffic u lt
because
not
to
a re
w id th
p la tfo r m
c o n t r o lle d
c o n s id e r e d
a lo n g w i t h
w id th w i l l ,
e x p e r im e n ta l and a r c h a e o lo g i­
o f th e
in c lu d e d
c o n s t a n t due
a n a ly s is
F la k e
c o m p a r is o n s b e t w e e n t h e
t h a t w e re
can be
p r e p a r a tio n ,
in
Tabun,
F o r e x a m p le ,
M o re o v e r,
cal
has been
m o rp h o lo g y , w h ic h
s u rfa c e ,
r a d ia lly
or
as
it
a r c h a e o lo g ic a l m a t e r ia ls
s ig n ific a n t
fr o m
F ir s t,
e x p r e s s m uch m o re u n c o n t r o l l e d
c o re
c o re
It
above0
o f s e v e ra l d iffe r e n t
Second,
fla k e
a
fla k e s
to
e x te r io r
on th e
e x p e r im e n t ,,
B ecause
th e
s ta te d
th e
in
d e s ig n
and
a d d itio n
th e
c o n t r o lle d
o f th e
fla k e
be an
e x te r io r
w id th .
o f c o u rs e ,
be
to
th e
a n g le
c o n s id e re d
la t te r
e x p e r im e n t
P la tfo r m
o f h is
in d e p e n d e n t v a r i a b l e ,
p la tfo r m
th e
e x p e r im e n t a l c o r e s ) .
b y th e k n a p p e r as p a r t
to
w ith in
w id th ,
p la tfo r m
and in c lu d e d
and p la tfo r m
th ic k -
as a dependent
v a r ia b le .
The
g o a l h e re
pen d en t v a r ia b le s
p la tfo r m
is
e x a m in e
o f e x te r io r
w id th w it h
th e
p la tfo r m
r e la tio n s h ip s
a n g le ,
dependent v a r ia b le s
p la tfo r m
o f le n g th ,
b e tw e e n
th e
th ic k n e s s
w id th ,
and
in d e ­
and
84
thicknesso
There are a number of ways of doing this*
Because it is
desirable to discover how each of the individual dependent variables is
affected by aspects of the platform preparation, multiple regression is
again the most useful techniqueo
Table 29 and Figures 15? 16, and 17 present the results of this
analysiso
The multiple r and R-square values, while lower than those
obtained with the experimental data, are quite significant0
They are
lower, of course, because it is not possible to include or control for
the effects of other independent variableso
By examining the standard­
ized Beta's in Table 29 it is possible to see that length appears to
be most strongly affected by exterior platform angle; width by platform
width; and thickness by platform thickness= This is also suggested
through partial correlation analysis (see Table 30, whereby comparisons
between each dependent variable are made with one independent variable
while controlling for the effects of the other two independent variables0
There are a number of issues to be addressed concerning these
regression models= First, examination of the residuals shows a slight
curve in the data which is not accounted for by a linear modelo
This
curve may be a result of the fact that exterior platform angle is, by
definition, related to flake dimensions according to a circular func­
tion = However, attempts to fit this curve through changes in the
regression model have so far been unsuccessful, probably because of
the inability to control other independent variableSc
Also there is a problem of multicolinearity brought on by the
fact that two of the independent variables, platform thickness and
platform width, are significantly correlated with each other (r = .668)0
85
Table 2 %
Multiple correlations of exterior platform angle, platform
width and platform thickness with (A) length, (B) width,
and (C) thickness (Tabun sample)„
Multiple r = .4292
R-square = .1842
(A) Length
df
regression
residual
total
3
507
510
Variable
EPA
PW
PT
B
Analysis of Variance
Sum Squares
Mean Square
30764.6
I36204.I
Standard
Error
B
Standardized
Beta
.075
.8271
2.7436
.4459
-.031
.256
.774
-.5187
14.02
Multiple r = 06026
regression
residual
total
27390.6
48049.8
F
107.134
.393
26.102
Signifi­
cance
<.01
<.01
<=01
F
913002
96.3
94.74
510
B
Standard
Error
B
.044
.491
1.63
.2583
5.401
8.785
Standardized
Beta
.2041
.4749
.2384
(C) Thickness
F
28.753
120.87
29.063
Signifi­
cance
<.01
<.01
<=01
R-square = ,
.3483
Multiple r = .5902
regression
residual
total
26806
Analysis of Variance
Sum Squares
Mean Square
3
507
Variable
EPA
PW
PT
38.2
10254
R-squajre = ,
.3730
df
(B) Width
F
df
.3
507
510
Analysis of Variance
Mean Square
Sum Squares
2713.4
5077.2
90405
10.0
F
90=3
86
Table 29— Continued
(C) Thickness continued
Variable
EPA
PW
PT
B
=097
-=179
7=73
Standard
Error
B
Standardized
Beta.
=014
=159
=2581
-=0489
44=92
1=25
<=01
= =263
06528
212=85
<=01
=529 '
F
Significance
8?
133
120
107
LENGTH
94
ee
•• e»
66
##**##**»##»****»*
# **#*»
•
42
29
29
35
41
47
53
59
ESTIM ATED
Figure 15«
65
71
77
63
LENGTH
Scatter diagram of length (in millimeters) to estimated
length based on exterior platform angle, platform width,
and platform thickness for combined Tabun samples. —
See Table 29.
89
88
102
•2
•2
72
•2
WIDTH
62
•• •
•••
*#** «* « *»
»*»»####*» • •
42
•• **##»»» *»• •
***# *#»* • ••
••»••••• •» * »#*
% #«#»*#»%»* ••
62
22
22
30
38
46
54
E S T IM A T E D
Figure 16.
62
70
78
86
94
WIDTH
Scatter diagram of width (in millimeters) to estimated
width based on exterior platform angle, platform width,
and platform thickness for combined Tabun samples. —
See Table 29.
102
89
28
THICKNESS
22
#•••• ••
**»#***»«#»»»*
•
2
4
• •
M
• #— I
••
6
8
10
ESTIMATED
Figure 17.
12
14
16
20
22
THICKNESS
Scatter diagram of thickness (in millimeters) to esti­
mated thickness based on exterior platform angle,
platform width, and platform thickness for combined
Tabun samples. — See Table 29.
90
Table 30o Partial correlations for length, width, and thickness with
exterior platform angle (EPA), platform width (PW), and
platform thickness (PT), controlling for two of the three
independent variables (shown in parenthesis)=
EPA
(PT,PW)
PW
(EPA,PT)
Length
=4159
-=02?0
=2200
Width
=2233
=4489
=2274
Thickness
=2798
-=0376 .
PT
(EPA,PW)
=5583
91
This correlation is to be expected given the f1intknapping process (see
the discussion in Chapter 4), and so it cannot be eliminated from the
data.
However, this problem does affect the parameter estimates, making
them less reliable» This is one reason why the emphasis in this dis­
sertation is on the strength of the relationships (r and R-square) and
not on the regression coefficients themselveso
Another problem affecting these coefficients has been stressed
repeatedly, namely the exclusion from the analysis of the other known
independent variables that affect flake dimensionso
When all of the
various industries from Tabun are combined, as in the preceding analy­
ses, the implicit assumption is that these excluded independent vari­
ables are constant throughout the sequence —
an assumption that
probably is not correcto
One way to observe the hidden effects of these excluded vari­
ables on the estimators is to perform the same regression on each
separate industry and observe the variation in coefficients (see Table
31)o For nearly every industry the relationship between the dependent
variable and one independent variable, relative to the other two inde­
pendent variables, is similar0 That is, in every industry the highest
association (as expressed by the standardized Beta's) is between flake
thickness and platform thickness,.
In nearly every industry, flake
length is associated most highly with exterior platform angle, and
flake width most strongly with platform width,.
However, the actual
values for these Beta's vary considerably, presumably as the excluded
independent variables vary,,
92
Table 31°
Standardized Beta coefficients of independent variables for
each dependent variable by Tabun IndustrieSo
Standardized Beta's
EPA
PT
PW
Industry
Variable
Upper
Mousterian
Length
Width
Thickness
.325
.. o282
.237
.106
Length
Width
Thickness
Lower
Mousterian
Transo
Mousterian
Amudian
Upper
Yabrudian
Upper
Acheulian
Lower
Yabrudian
Bed
90
Multiple
R
N
68
68
68
.377
.338
.004
.389
.055
.515
.351
.285
.473
.445
.798
.I06 .369
-.095
.521
.659
Length
Width
Thickness
.223
o22k
.148
.326
—.196
.151
=327
=655
=696
-.082
0682
0626
Length
Width
Thickness
.314
.219
.275
=466
-.302
.4oo
.267
=428
-.042
.609
.621
Length
Width
Thickness
.522
.658
.107
.801
=076
.487
.741
.761
—=096
.725
Length
Width
Thickness
.459
.099
.459
=107
.015
.449
=324
.612
-.005
.330
-.025
Length
Width
Thickness
=511
.249
=456
.549
.278
.116
.519
.655
56
.683
0696
.016
.697
56
56
Length
Width
Thickness
.317
.167
65
.215
=748
.150
.330
=.100
=322
.298
.461
.640
65
65
.397
=507
.423
.191
.688
.512
=430
.685
.676
82
82
82
58
58
58
70
70
70
53
53
53
58
58
58
93
To some extent it is also possible to control exterior core
morphology, for at least a sample of the Tabun materials^
One of the
variables recorded by Jelinek in the course of his analysis is flake
form, which has two values for flakes showing evidence of blade preparation0
Assuming that the surface morphologies of, these flakes are
roughly the same, with longitudinal parallel flake scars along the
exterior surface, it is possible to control for core morphology and
repeat the multiple regression for this sample where form is either
first or second order bladeo
When this is done (see Table 32), there
is a significant increase in the correlation coefficients for length
and width, although less so for thickness» Again, the coefficients
vary from those obtained earlier, but the nature of the relationships
remain similar0
Canonical correlation analysis provides another means of deter­
mining relationships between the independent and dependent variables6
The purpose of this technique is to compare the set of independent
variables with the set of dependent variables (see Van de Geer 1971)=
In other words, canonical correlation analysis does not determine the
relationship of length alone to the set of independent variables, but
rather the set of length, width, and thickness to them0 The results of
this analysis, which are presented in Table 33, basically support the
preceding analysiso
In the first canonical variate, platform thickness
and flake width and thickness all have high loadings0 Platform width
is clearly correlated with flake width in the second variate, and in
the third variate the two highest loadings are for exterior platform
94
Table 32o Multiple correlations for (A) length, (B) width, and (C)'1
thickness for all blades for Tabun sample o
Multiple r — 06266
(A) Length
R-square = =2773
Analysis of Variance
Sum Squares
Mean Square
df
regression
residual
total
B
Variable
EPA
PW
PT
6822=4
17782=9
3
104
107
Standard
Error
B
o5229
=152
7.361
7=968
2=284
5=519
Multiple r = O68o4
regression
residual
total
3
104
107
B
Variable
EPA
PW
PT
=2993
=2992
11=894
=2670
7=7377
2970.3
3445=7
Standard
Error
B
=064
=950
2=359
=1949
5=770
7=425
Variable
EPA
PW
PT
Signifi­
cance
<=01
<=01
<=01
990=1
31 =9
F
=2233
=4934
9=2212
36=881
=2632
9=902
F
31=1
Signifi­
cance
<=01
<=01
<=01
R-square = .
=3742
Analysis of Variance
Mean Square
Sum Squares
df
regression
residual
total
10=381
Standardized
Beta
Multiple r = 06117
(C) Thickness
F
13=3
R-square = =4630
Analysis of Variance
Mean Square
Sum Squares
df
(B) Width
Standardized
Beta
2274=1
170=9
F
386=1
3
104
645=8
128=7
5=7
F
22=5
107
B
Standard
Error
B
o0657
=026
=7385
5=903
=396
=989
Standardized
Beta
=1867
=1599
=5268
F
5=82
3=471
35=6209
Signifi­
cance
= =017
= =065
<=01
95
Table 35°
Canonical correlation analysis of length, width and thickness
with exterior platform angle, platform thickness and platform
width (N .= 510) o
Canonical
Variate
Eigenvalue
1
2
5
o4l?64
o21435
011564
Canonical
Correlation
D=F=
=64625
=46317
=34005
Variate 1
9
4
1
Coefficients
Variate 2
Significance
<=01
<=01
<=01
Variate 3
Dependent Variables
Length
Width
Thickness
o14670
=58650
=52301
=44503
-=91995
=73765
-=92847
049538
=43407
=81177
-1=05085
-=84844
=50414
-=48332
-=32896
=74653
Independent Variables
EPA
PT
PW
=80284
038443
96
angle and flake length»
So, in general, this analysis is in agreement
with the results obtained through multiple regression0
As was the case in the controlled experiment, increasing the
exterior platform angle affects the relationships between other charac­
teristics of the platform and flake dimensions» Table $4 shows corre­
lations between flake width and thickness and platform width and
thickness by intervals of exterior platform angle»
It is possible to
see that, especially for thickness, the correlations tend to decrease
as exterior platform angle increaseso
Thus, again, the multiple
correlations presented in Tables 29, 31 and 32 are, in effect, averages
over the entire range of exterior platform angles<,
In the controlled experiment it was found that increasing the
exterior platform angle resulted in a decrease in the platform thick­
ness that would allow the successful detachment of a flake0 Table 35
shows that the same is true for the Tabun flakes, and that it is true
for platform width and platform area (ioCo, the product of platform
thickness and platform width) as wello
Given such close agreement between the archaeological and
experimental material, it is possible to conclude that a large portion
of the dimensional variability exhibited in the Tabun collection is
explained by variation in platform preparation in terms of exterior
platform angle, platform thickness and platform widtho
The controlled
experiments allowed us to determine the precise relationships between
the variables that can be controlled by the knapper and those observable
on the resulting flakeso
These same relationships exist for archae­
ological materials, and thus it is possible to understand some purely
97
Table 3^°
R-square values computed for flake width and platform width
and for flake thickness and -platform thickness by intervals
of exterior platform angle0- — Tabun sample, sample sizes
in parenthesise
Exterior
Platform Angle
Width -PW
50-55
-753
.812
( 9)
(11 )
.314
-734
(22 )
(29)
-564
-734
(48)
(58 )
-345
(64)
.450
(75)
.144
-365
(93)
(117)
-391
(132)
.389
55-60
6 0 -65
65-70
70-75
75-80
\
80-85
85-90
90-95
.138
Thickness -PT
(159)
(96)
-305
(116 )
=306
.297
(52)
(58)
-079
(21 )
-235
(26 )
98
Table 35°
Median platform width, platform thickness, and platform area
(platform width x platform thickness) by intervals of
exterior platform angle for Tabun0 — All dimensions in
centimeters=
E x te r io r
P l a t f o r m A n g le
P la tfo r m
W id t h
50-55
3°490
1.230
4.060
(11)
(11)
(11)
2.770
1.063
2.901
(30)
(30)
(30)
2.849
=902
2.706
(57)
(58)
(57)
2.712
.920
2.555
(72)
(75)
(72)
2.254
.762
1=589
(115)
(118 )
(115)
2.008
.740
1.413
(155)
(159)
(155)
1=940
.632
1.166
(113)
(118 )
(112)
1 .7 8 0
.562
1.051
(57)
(58)
(56)
2.030
.645
1.260
(27)
(27 )
(27)
1=973
=395
.710
(12)
(12)
(12)
55-60
60-65
65-70
70-75
75-80
80-85
85-90
90-95
95-100
P la tf o r m
Thickness
P la tf o r m
A re a
technological effects on prehistoric lithic assemblages= With this
knowledge, it should be possible to isolate some of the strategies used
by prehistoric knappers to obtain certain kinds of flakeSo
CHAPTER 4
TECHNO LO GICAL S T R A T E G IE S AT TABUN
In
th e
la s t
c h a p te r
v a r ia tio n
in
m a te r ia ls
can be e x p la in e d
s o le ly
by
th e
th o u g h
th e s e
th e
v a r ia b le s ,
a re
in
in d e p e n d e n t v a r i a b l e s
fla k e
p o s s ib le
fo r
th e y
of
a c o re
la r g e ly
k in d s
d e r iv e d
v a r ia b le s
fla k e
o f th e
A l­
p r e p a r a tio n
d im e n s i o n s 0
o f e ffo rts
c o n tr o lle d
k n a p p e r,
r e fle c tio n s
lith ic
re m o v a l0
co n c e rn e d w ith
fla k e
a c c u ra te
show t h e
fo r
a c tio n s
a ffe c tin g
a re
c e r ta in
th e
th e y
In
of
a re
m any w a y s ,
o f w hat th e
he u n d e rto o k b e fo re
w as re m o v e d *
now t o
k n a p p e rs *
to
a s a w h o le
b e tw e e n th e
each
p e rfo rm
in
r e s u lts
d is c u s s
B e fo re
n e c e s s a ry
fla k e S o
b a s is
d e p e n d e n t upon th e
B a s e d on th e
th e
w h ic h a r e
t h a t m uch o f
o f a r c h a e o lo g ic a lly
k n a p p e r a s he p r e p a re s
k n a p p e r w a n te d ,
th e
on th e
in d e p e n d e n t v a r i a b l e s
th e s e
was d e m o n s tra te d
d im e n s io n a l a t t r i b u t e s
p la tf o r m ,
tru e
it
o rd e r
th e
p re s e n te d
k in d s
s e p a ra te
a d d itio n a l
to
in d e p e n d e n t v a r i a b l e s
im p o r t a n t e f f e c t
e x p e r im e n t s ,
it
is
s ta tis tic a l
a re
and o th e r
r e la te
c h a p te r,
used by
e x a m in e d ,
a n a ly s e s
th e
o f th e
it
c o n t r o lle d
on f la k e
c le a r
le n g th *
th a t
to
th e
is
Tabun
h o w e v e r,
o b s e r v a b le
p r im a r ily
h a s b e e n sh ow n t h a t
is
p r e v io u s
it
is
m a te r ia l
d is c o v e r w h e th e r a d d i t i o n a l r e l a t io n s h ip s
These r e la tio n s h ip s
it
th e
s tr a te g ie s
in d u s tr y
in d e p e n d e n t v a r i a b l e s
F ir s t,
of
in
fe a tu re s
e x is t
o f th e
m e a n s b y w h ic h
b y th e k n a p p e r0
e x t e r io r p la tfo r m
a n g le
has an
B a s e d o n my own r e p l i c a t i v e
th e re
a re
100
s e v e r a l w ays o f c o n t r o ll in g
101
th is
a n g le o
s tr ik in g
fa c e =
s u rfa c e
F ig u r e
have
h ig h
d e s ig n
o f th e
p e rfo rm
o n ly
th e
to
th e
th e
th e
s m a ll
fla k e s
l 8b ) o
T h is
fa c e t in g
a h ig h
th a t
r e la tiv e
t y p ic a l p r is m a tic
to
fla k e s
re m o v e d
p la tfo r m
a n g le s
s im p ly b e c a u s e
W it h
such a c o re ,
m o s tly
b la d e
fr o m
th e
on th e
th e
in te n d e d
th e
fla k in g
c o re ,
th is
of
s u r­
such as
ty p e
th e
o f c o re
b a s ic
k n ap p er w i l l have
fla k in g
is
s u rfa c e ,
to
fo r
fla k e o
a re
s u rfa c e .
m any t y p e s
s u rfa c e
W it h
e x t e r io r p la tfo r m
th e
a c tio n - i s
in
a n g le
so
th e
m a jo r s t r i k i n g
r e s u lts
c o re
of
its e lf«
th e re
fr o m
a
a
m in im a l p r e p a r a t i o n s ,
fla k in g
ra is e
p re p a re
is
A ll
e x te r io r
c o re
to
a lw a y s a t
l8a<>
H o w e v e r,
w h ic h
is
o f th is
re m o v a l o f each
in
th e s e
is
A n e x a m p le
sh ow n i n
w ill
One o f
th is
a n g le
p la tf o r m
c a lle d
h ig h e r
o f c o re s ,
m ay b e
ty p e
fo r
s it u a t e d
o f c o re ,
it
any p o te n tia l
s u rfa c e
fa c e t in g
e x te r io r
such as L e v a llo is
near
th e
th e
p la tfo r m .
p la tf o r m
at
m uch l o w e r a n g l e s
is
p o s s ib le
fla k e
c o re
c o re s ,
edge
to
b y r e m o v in g
(s e e F ig .
T h a t p la tfo r m
a n g le s
is
show n i n
T a b le
3 6 , w h i c h , u s i n g t h e T a b u n m a t e r i a l , c o m p a re s t h e m ean e x t e r i o r p l a t ­
fo r m
a n g le
p la in
fo r
p la tfo r m s *
a tte m p t
e x te r io r
re m o v e
at
is
F ro m
fa c e tte d
th e s e
in c r e a s e
It
s h o u ld be p o i n t e d
b e tw e e n
p la tfo r m
e x te n t
a n g le
w ith
to
c o r r e la tio n
th e
fla k e s
th a t
it
s u ita b le .
tw o ,
any r a t e ,
th re e ,
it
th e
is
c le a r
o ut th a t
it
a c t u a l num ber o f
a n g le .
It
it
e x t e r io r p la tfo r m
th e
is
d a ta
p la tf o r m s
O b v io u s ly
n e c e s s a ry ,
m a tte rs
o r even 20
seem s f a i r
to
fla k e s
th a t have
th a t
fa c e tin g
r e fle c ts
little
is
n o t n e c e s s a ry
fa c e ts
fa c e ts
to
to
c o n c lu d e
an
a n g le .
and
th e
to
v a lu e
expect a
o f th e
f a c e t i n g w o u ld o n l y b e p e r f o r m e d
i.e .,
fa c e ts
w ith
th e
a re
re m o v e d u n t i l
to
th e
k n a p p e r w h e th e r he m ust
o b t a in
th e
c o r r e c t a n g le .
t h a t p la tf o r m
fa c e t in g
But
102
ERA ^
B
F ig u r e
18.
E x t e r i o r p la t f o r m a n g le on d i f f e r e n t c o re t y p e s . —
( A ) D r a w i n g o f i d e a l i z e d p r i s m a t i c c o r e s h o w in g c o n s t a n t
e x te r io r
p la tfo r m
a f t e r fa c e tin g
(d a s h e d l i n e ) .
to
a n g le s .
(B )
show c h a n g e
L e v a llo is
in
e x te r io r
c o re
b e fo re
p la tfo r m
and
a n g le
103
Table 36=
Mean exterior platform angles for plain versus facetted
p la tfo r m s ,—
Platform Type
t = -7 ,3 5 ,
P <% 0 1 ,
a s s u m in g u n e q u a l v a r i a n c e s .
________ Exterior PlatformA n g l e _______
Mean
S,D,
N
Plain or dihedral
73=77
10,66
467
Facetted
79=70
9=03
218
104
re p re s e n ts
a n g le ,
a p a r tic u la r
w h ic h
in
s tra te g y
fo r
c o n tr o llin g
tu rn
s tr o n g ly
a ffe c ts
th e
B a s e d on t h e
p r e v io u s
a n a ly s is ,
th e
e x te r io r
d im e n s io n s
o f th e
p la tf o r m
r e s u ltin g
fla k e o
sh ow n t o
is
be a n im p o r t a n t
little
p r im a r ily
p la tfo r m
v o lv e d
doubt th a t
a c c o r d in g
s u rfa c e 0
in
to
p la tfo r m
t r im m in g
o f th e
p la tf o r m
to
th is
p la tf o r m e
it
th ic k n e s s ,
p la tfo r m
s u rfa c e
over
m ay h e l p
th e
p la tfo r m
th ic k n e s s e s
w h ic h
is
a s m a ll p la t f o r m
punch i s
p o s s ib le
r e s u lts
d ir e c t
a re
v a r ia b le
in
is
by
edge he
little
th e
T h e re
knapper
s tr ik e s
th e
p r e p a r a tio n
in ­
does n o t
it
in
does s e rv e
to
th e
ju d g e
w h ic h
is
t r im m in g o
fro m
its e lf
to
in d ir e c tly
th e
o f th e
d is ta n c e
e x te r io r
d ir e c tly
re m o v e
r e s u lt
T h is
p r o d u c in g
T h e re
th ic k n e s s
th e
use
o f an in d ir e c t
c o n tr o llin g
th e
a c c u ra c y
such as
m eans o f
is
fo r
d e s ir e d .
r e fle c te d
a s k ille d
a re
o th e r
U n fo r tu n a te ly ,
on th e
fla k e
flin tk n a p p e r
in
in
c e r ta in
fo r
punch,
o f a b lo w w h en
th e
use
of a
and i t
o b ta in
is
id e n tic a l
p e r c u s s io n .
in
th e
p r e v io u s
d e te r m in in g
fla k e
c h a p te r,
w id th .
In
p la tf o r m
w id th
flin tk n a p p in g
is
c o n tro l
th is
v a r ia b le ,
One o f t h e s e
is
to
a
th e re
'
s e v e r a l w ays to
a
tu rn
s tr a te g ie s
its e lf,
to
s id e
a n y o v e rh a n g o f th e
c o re .
fo r
r e la te d
P la tf o r m
m o re a c c u r a t e l y .
As d e m o n s tra te d
c r itic a l
i
c o re
has been
th ic k n e s s o
c o n tr o lle d
fla k e s
s u rfa c e
c le a r ly
o c c a s io n a lly
fla k e
p la tfo r m
e x te r io r
th ic k n e s s
n o t a lw a y s
w ith
th e
flin tk n a p p e r
a ti e f f e c t i v e
th e re
re m o v a l o f s m a ll
A lth o u g h
p la tfo r m
th is ,
such as e x t e r io r
s m a lle r p la t f o r m
c o n tr o llin g
fr o m t h e
m ay b e p r e p a r a t i o n
t h ic k n e s s ,
th e
th a n
in
is
to
th ic k n e s s
a ttr ib u te =
th e re
in v o lv e s
r e la tin g
th ic k n e s s
how f a r
O th e r
v a r y in g
H o w e v e r,
v a r ia b le
p la tfo r m
ta k e
105
a d v a n ta g e
o f a r e la tio n s h ip
ness
e x is t s
th a t
fo r
r e g u la r
th a t
see
in c r e a s in g
th e
p la tfo r m
w id th
A to
p o s s ib le
to
p la tfo r m
w id th
of
*6 6 8
(s e e F ig *
fr o m
e x te r io r
edge
o f th e
th e
in c r e a s in g
th ic k n e s s
la r g e
fr o m
o b ta in
and w id th
th a t
H o w e v e r,
fr o m T a b u n
d ip
or
T h is
fa c e
B*
In
at
th e
in c r e a s in g
fla k e
th ic k n e s s *
a lo n g
p la tf o r m
c o re
it
T h is
th e
edge
tr im m in g
th a t
th e
n e g a tiv e
s u p e r im p o s e d o v e r
th e
b u lb
p o s itiv e
W hen s u c h a c o n c a v i t y
r e s u ltin g
fla k e *
s e n te d
in
T a b le
fla k e s
w ith
F ir s t,
37
c le a r ly
concave
th o s e
fla k e s
w ith
th re e
m illim e te r
it
in c r e a s in g
p o in t
edge
of
to
o f th e
p ro d u c e d ,
in
sh ow t h a t
p la tfo r m
o f p la tf o r m
th e
in
th e n ,
th e
fla k e
in
fla k e s
p r o d u c tio n
p la tf o r m
th e
th e
la te r
is
de­
of a
(s e e F ig *
2 1 )*
by
T a b u n m a te ­
sam e p l a t f o r m
fla k e
s u r­
d ir e c tly
n e x t*
it
has
th in n e r
tw o e f f e c t s
fla k e s *
th ro u g h o u t th e
edges a re
edges*
and
(i.e * ,
b o th
m ay b e p r o d u c e d e i t h e r
fr o m
is
d is ta n c e
and s im u lta n e o u s ly
o f th e
o f a p r e c e d in g
is
th e
in c r e a s e
in v o lv e s
fla k e s
it
th e
th ic k e r *
c o m m o n ly i n
b u lb
in c r e a s e
o f p e r c u s s io n
o b s e r v a b le
fla k e s
s tra te g y
co n v ex p la tfo r m
in te r v a l
by
and
to
th ic k n e s s
T h i s w o u ld r e s u l t ,
of
r e s u lts
e x te r io r
fro m T a b u n ,
p o s s ib le
m o re
p o s s ib le
d a ta
is
c o n c a v ity
o r,
is
b e tw e e n p la t f o r m
s tra te g y
19,
th e
th e
e x te r io r
F ig u r e
D w ill
to
th e w id th
to
C to
b o th w id e r and
a n o th e r
it
th ic k ­
fr o m
Thus,
sam e t i m e =
b y r e m o v in g a s u c c e s s io n
so
2 0 )*
and p la tf o r m
c o n s ta n t,
u s in g
c o r r e la tio n
w id th
R e fe r r in g
th ic k n e s s
a b s o lu te ly
is
h e ld
fa c t,
th ic k n e s s ),
a re
p la tfo r m
a re
p la tfo r m
fo r
e x te r io r
r ia ls ,
fa c to rs
s im p le
th e re
c o n c a v ity
e x te r io r
a
p la tfo r m
fla k e s
c r e a s in g
o th e r
convex c o re s *
a s s u m in g
th a t
a ll
b e tw e e n p la t f o r m
T a b le
th ic k n e s s ,
The
on th e
d a ta p r e ­
T a b u n s a m p le s ,
a b s o lu te ly
th in n e r
th a n
38 s h o w s t h a t f o r e a c h
fla k e s
w h i c h do
106
1— A -""4
I
F ig u r e
19.
I
Two i d e n t i c a l c o r e s w i t h f l a k e s o f d i f f e r e n t p l a t f o r m
t h ic k n e s s e s re m o v e d . — G iv e n n o rm a l c o r e g e o m e tr y ,
i n c r e a s i n g t h e p l a t f o r m t h i c k n e s s fr o m C t o D w i l l
i n c r e a s e t h e p l a t f o r m w i d t h fr o m A t o B .
107
2 .5 0
2 .2 6
2.02
PLATFORM
THICKNESS
1 .7 9
1.54
1.07
N- 430
83
••• •
e eeee ••
r « .668
.6 0
R ■. 4 4 6
36
.4 2
LI2
1.81
2.51
3.90
PLATFORM
F ig u r e
20.
4.60
6.6 9
WIDTH
S c a t t e r d ia g r a m o f P l a t f o r m T h i c k n e s s w i t h P l a t f o r m
W i d t h ( i n c e n t i m e t e r s ) f o r c o m b in e d s a m p le fr o m T a b u n .
7.39
108
B
F ig u r e
21.
Shape
of
e x te r io r
p la tfo r m
fo r m s u r f a c e ( t o p ) a n d fr o m
(A ) C o n cave p la t f o r m e d g e .
e d g e v ie w e d
th e
(B )
to w a rd
th e
p la t­
s id e ( b o t t o m ) . —
C onvex p la tf o r m e d g e .
109
Table 37»
Flake thickness by platform shape= •—
assuming unequal varianceSo
Shape of Exterior
Platform Edge
t = —4 .93 ? p <.01,
Mean Thickness
S .D .
N
Concave
7 o96
3-78
188
Convex
9.62
4.82
626
Table 38. Mean flake thickness broken down by intervals of platform
thickness and platform shape0
Platform
Thickness
sj
1
0
031-061
061-091
091-1021
lo21-1 =51
Shape of
Exterior
Platform Edge
Flake Thickness
S .D .
Mean
N
t-test
(1-Tail P)
Concave
Convex
6089
1.93
4.10
13
45
-2.42
(P = .01)
Concave
Convex
6.43
7-55
2.90
4.62
63
186
-2.46
(P <.01)
Concave
Convex
8=29
9-05
3-01
62
4.13
169
Concave
Convex
10ol7
11.05
3-76 .
3=76
121
Concave
Convex
11.25
12.83
2.96
8
4.10
69
4,92
24
-1.36
(P <.09)
- -77
(P <=23)
—1062
(P <=06)
110
exhibit concave exterior platform edges are thinner than those which do
not0 Although the differences in thickness are not significant at the
o05 level for each interval, the consistency of the comparisons suggests
that the relationship between platform dipping and flake thickness
exists independently of platform thickness0 The probability of obtain­
ing these differences in flake thickness for each interval if the
variation were random is the product of the probabilities of each inter­
vale
The conclusion can therefore be reached that by using the tech­
nique of platform dipping, one is able to utilize a higher platform
thickness (which possibly makes it easier to strike the flake) yet
still decrease the absolute thickness of the flake=
Second, the production of a concave exterior platform edge makes
it possible to retain a relatively high platform width*
It can be seen
from Table 39 that such flakes have higher platform widths than those
flakes which have convex platform edges for any given interval of
platform thickness*
Thus, it should be clear that by using this tech­
nique, the knapper overcomes the more normal direct relationship be­
tween platform thickness and width shown in Figures 19 and 20*
In this
way it is possible to produce flakes that are wider, yet thinner, than
those that result from the use of other techniques*
We c a n now s e e
to
p r e h is to r ic
fe a tu re s
th a t
of
th e re
b u t have
p ro d u c ts *
a re
a num ber o f te c h n iq u e s
t h a t e n a b le
At
th is
th e m t o
p o in t
it
s e v e r a l in d e p e n d e n t v a r i a b l e s
n o t b een in c lu d e d
and e x t e r i o r
th e re
flin tk n a p p e r s
th e ir
a re
th a t
c o re
in
th is
m o r p h o lo g y *
The
.
a n a ly s is *
r e s u lts
is
th a t
c o n tro l
c e r ta in
im p o r t a n t
th e
so
to
fo rm a l
re p e a t
k n a p p e r c o n tr o ls
P r im a r ily
o b ta in e d
a v a ila b le
th e s e
fa r
a re
do n o t
fo rc e
Ill
Table 39°
Platform
Thickness
.Ol-o31
.31-°6l
°6l—.91
.91-1=21
1.21-1.51
Mean platform width broken down by intervals of platform
thickness and platfdrm shape„
Shape of
Exterior
Platform Edge
Platform Width
Mean
S.D.
N
t-test
(1-Tail P)
(P <°01)
5=62
Concave
Convex •
2.04
063
1.00
-39
15
45
Concave
Convex
2.34
1.60
-75
=72
188
(P <°01)
Concave
Convex
3-10
2.19
=91
.78
64
170
7=30
(P <.01)
Concave
Convex
3-46
1=04
2.56
085
24
124
4.48
(P <=01)
4.74
1.08
.89
9
70
4.17
(P <.0l)
Concave
Convex
3.20
64
7.12
112
necessarily lead to the conclusion that these other independent vari­
ables are not important in affecting flake form.
Rather, the point
should be taken that it is possible to understand metric variability in
flakes to a significant extent by employing those independent variables
that are readily observable and quantifiable on the flakes themselves.
We now turn our attention to comparisons between the various
Tabun industries to examine differences that can be discerned in spe­
cific technological strategies.
Two analyses are presented here.
The
first illustrates the potential for explaining differences in flake
dimensions on the basis of the kinds of platform preparation already
discussed.
The second, restricted to the Levallois industries of Tabun,
is an exploratory analysis designed to include other aspects of flake
morphology in an attempt to interpret industrial relationships.
For purposes of the first study, the primary dependent vari­
ables of concern are the dimensional attributes of the flakes; that is
length, width, and thickness.
Figure 22 is a three-dimensional graph
of the industries according to their mean values of these dimensions
(for the actual values, see Table 40),
It is clear that there are real
differences between the industries as reflected by these dimensions.
It is possible to explain these differences on the basis of the
strategies used to control the independent variables, i,e,, exterior
platform angle, platform thickness and platform width.
Figure 23 is a
similar three dimensional graph of the values of these major inde­
pendent variables in each industry.
sented in Table 4l,
Actual values for these are pre­
In both Figures 22 and 23 the lines that divide
LY #
AC
• XIV
• TR
< >
THICKNESS
AM
42
38
7 -
34
LM
30
50
55
60
65
70
LENGTH
Figure 22.
113
Three-dimensional graph of mean values of length, width, and
thickness (in millimeters) of eight samples of complete flakes
from Tabun.
114
Table 40o Basic dimensional data for the eight samples from Tabrnio
In d u s tr y
M ean L e n g th
(N )
M ean W id th
(N )
M ean T h ic k n e s s
(N )
U pper
M o u s te r ia n
64o58
(102)
37-42
(92)
7-29
(109)
Low er
M o u s te r ia n
70.19
(111)
28.13
(109)
(115)
T r a n s itio n a l
M o u s te r ia n
61.21
(98)
37-90
(103)
9-27
(120)
65.04
' (104)
31-92
(109)
(120)
Upper
Y a b r u d ia n
56081
(83)
40.84
(83)
11=24
(110)
A c h e u lia n
54.56
(100)
38.25
(102)
9-57
(120)
Low er
Y a b r u d ia n
55-64
(101)
40.93
(88)
10.49
(114)
U n i t X IV
50.816
(87)
33-369
(103)
9-74
(120)
A m u d ia n
6.83
9-00
115
LY
UY
1.00 1
.95 "
< >
THICKNESS
.9 0 -
UM
.8 5
AC
2.9
2 jB
PLATFORM
2.7
2.6
TR
2.5
-n
-
XIV
vua'*
.75
2.3
LM
.70
-
2.1
2.0
65
70
75
EXTERIOR
Figure 23«
60
PLATFORM
ANGLE
Three-dimensional graph of mean values of exterior
platform angle (in degrees), platform width, and
platform thickness (in centimeters) of eight samples
of complete flakes from Tabun.
116
Table 4lc Basic platform data for the eight samples from Tabun0
Mean EPA
(N)
Mean PW
(N)
Mean PT
(N)
Upper
Mousterian
81=78
2=620
(92)
(107)
.773
(108)
Lower
Mousterian
78=93
(94)
2=035
(108)
(112)
Transitional
Mousterian
76=46
(79)
2=335
(104)
(104)
Amudian
77.47
(85)
2=080
=722
(113)
(113)
Upper
Yabrudian
72=94
(83)
2=758
(103)
.931
(107)
Acheulian
73.80
(79)
2=309
(106)
.771
(106)
Lower
Yabrudian
70.31
(86)
2=876
(103)
(no)
Unit XIV
72=74
(87)
2=047
(119)
.734
(116)
Industry
=710
=702
.993
117
the industries into groups are arbitrary and are intended to serve as
an aid in making comparisons between the figureso
As seen in Figure 22, the Mousterian industries and the Amudian
all show relatively high values of length» As we would expect, the
placement of these industries relative to the others is matched in
Figure 23 by their having higher exterior platform angles» Likewise,
those industries represented in Figure 22 that have wider flakes (the
Upper Mousterian, Transitional Mousterian, Acheulian and both examples
of Yabrudian) are also the industries that in Figure 23 exhibit the
highest platform widths<, The relative placement of these industries in
Figures 22 and 23 thus follow the patterns expected on the basis of the
analyses presented in Chapter 3°
An unexpected relationship occurs when we compare thickness
with the independent variables» Based on the evidence presented in the
preceding chapter, it should be expected that a consistent relationship
would exist between flake thickness and platform thickness=
In Figure
22 there are three groups of industries in terms of thickness» First,
are the Yabrudian industries, which exhibit very thick flakes»
In
fact, they do have the highest values of platform thickness= However,
while the Lower and Upper Mousterian industries both have Very low mean
flake thickness values compared to the more moderate Acheulian, Amudian,
and Transitional Mousterian industries, all of the non-Yabrudian
industries have roughly similar mean platform thicknesses» We would
expect, in this case, that since the two Mousterian industries have
the thinnest flakes they would also have the thinnest platforms0
118
These differences in flake thickness among the non-Yabrudian
industries are best understood through an examination of the occurrence
of concave exterior platform edges, which as was demonstrated earlier
in this chapter, aids in the production of thinner flakes.
Table 42
presents data representing the percentage of such concave platform edges
in each of the industries.
From these it can be seen that the two
definite Mousterian industries show a much higher emphasis on this
strategy.
This, then, is the reason why the two youngest Mousterian
industries have the thinnest flakes in spite of the similarities in
their platform thicknesses to the other non-Y abrudian industries.
These data show a close relationship between what the inde­
pendent variables would predict in terms of the dimensional attributes
of the flakes, and what actually occurs.
Obviously the relationship is
not perfect, largely because of inability to control for the other
important independent variables.
In spite of this, however, it is
possible to distinguish the different strategies utilized by the pre­
historic knappers to obtain particular results.
For most of the
industries we see a relatively straight-forward relationship between
the independent and dependent variables.
Through time this situation
slowly changes until in the Mousterian we see conscious efforts to
overcome these relationships in attempting to produce thinner, and
ultimately wider flakes.
This change is primarily the result of dif­
ferences in platform preparation.
These changes in strategy, as evidenced by changes in platform
preparation, have potential for explaining other aspects of metric
variability in the Tabun sequence.
For example, the unidirectional
119
Table 42=
Percentage of flakes with concave platform edges for each of
the eight samples from Tabun0
Industry
Percentage
N
Upper
Mousterian
40o0
95
Lower
Mousterian
35=6
101
Transitional
25°7
101
17°11
111
Upper
Yabrudian
23°1
104
Acheulian
22=1
104
Lower
Yabrudian
l8c8
101
Unit XIV
9=2
119
Amudian
'
120
trend through time in flake width relative to thickness that was dis­
covered by Jelinek (I98O; see Fig* 1) is most probably the result of
these factorso
Based on the data presented here, it may be possible to
suggest that this trend reflects a developing awareness of particular
methods for controlling flake manufacture0
Up to now the focus of this dissertation has been on explaining .
differences in flake dimensions»
It has been demonstrated that these
dimensions are, to a large extent, dependent on variables of the plat­
form 0 In order to explain dimensional differences, then, one must look
to the independent variables that are responsible for producing those
differences*
Dimensional variability is, however, only one aspect of
assemblage variability*
At this point we will turn our attention to
other aspects of variability that exist among some of the Tabun indus­
tries*
This study is intended to be more exploratory in nature, that
is an analysis of some technological differences and the suggestion of
possible interpretations*
The next analysis focuses on the Levallois industries of Tabun,
which for our purposes includes the Amudian, the transitional Unit X
material, and the Upper and Lower Mousterian*
One intriguing question
regarding the Tabun sequence is the relationship between the Amudian
and Mousterian*
Chapter 2 presented some of the more evident differ­
ences between these industries in terms of typology*
Regarding the
manufacture of Levallois flakes, both the Amudian and Lower Mousterian
emphasized parallel flake preparation on cores for the production of
blades, while the Upper Mousterian material exhibits more radial core
preparation*
It has also been shown in the preceding study that
121
differences exist in terms of flake dimensions and particular aspects
of platform preparation,.
Three basic questions come to mind*
First, how useful are these
technological differences in distinguishing between the industries?
In other words, can an unknown assemblage be assigned to one or the
other industry on the basis of these variables?
If not, the second
question is what other technological variables would serve to distin­
guish them?
Finally, it must be asked what these differences mean with
regard to interpreting the relationships between the industrieso
To answer these questions, it is necessary to use a multivariate
statistical technique» The most appropriate one for this problem is
Discriminant Function Analysis, since we are dealing with a large
number of variables that vary differently within the different popula­
tions,
By employing discriminant analysis it is possible to determine
which variables are most useful in separating the industries.
For this analysis we will take as our three known groups the
Upper and Lower Mousterian samples and the Amudian; for the moment we
will disregard the Transitional Mousterian,
As a means of partially
controlling for other aspects of technology, only typological Levallois
flakes will be used.
The discriminant program employed is that con­
tained in SPSS, version 8=0 (Hull and Nie 1979)=
All program parameters
of the Discriminant procedure were left as default (see Nie et al,
1975s 446-456),
The program proceeds by first calculating linear co­
efficients of the input variables that result in the maximum inter­
group separation along two discriminant functions.
Then, discriminant
scores are calculated for each flake from those coefficients and the
122
cases plotted along the function axes.
In this way it is possible to
view group separation on the basis of the total population and not
simply the averages of their values.
The first question is how well do the differences described
above serve to separate the three industries.
Summaries of the dimen­
sional and platform data for the Levallois flakes are presented in
Table 43.
Figure 24 is a graphic representation of the three indus­
tries plotted according to their discriminant scores calculated on the
basis of these data.
It is clear from this that the separation between
the industries is not good.
Although there is a suggestion of direc­
tional change through time, it would not be possible to make reasonable
industrial assignments based on these variables alone.
However, there are other differences between the industries as
shown in Table 44.
viously.
Some of these variables have been discussed pre­
Platform faceting is related to the exterior platform angle,
but it seems clear that the Amudian employed this technique to a lesser
degree than did the Mousterian.
There is also less evidence of concave
platform edges and smaller platform areas.
exhibit fewer exterior flake scars.
The Amudian flakes also
Isolated flake scars represent
exterior scar remnants that are almost but not entirely obliterated by
subsequent core preparation prior to the removal of the observed flake
(see Appendix I).
Their occurrence may relate to particular kinds of
techniques employed in core preparation.
The percentage of isolated
flake scars is highest in the Lower Mousterian.
Transverse convexity
is computed by dividing the maximum flake height along the midtransverse section by flake width.
In effect, it is a measure of the
123
Table 43„
Basic dimensional and platform data for Levallois flakes
from Tabrnio — Mean, S 0Do, No
Industry
Length
Width
Thickness
EPA
PT
PW
Upper
Mousterian
67.1
20=7
(62)
38=7
12=7
(56)
6=65
2.76
(65)
82=7
'7=71
(56)
=749
=259
(68)
2=79
loll
(69)
Lower
Mousterian
73-1
17-3
(83)
27-0
79=7
7=97
(69)
=664
=219
(81)
2=02
7-77
(80)
6=53
2=47
(85)
71-6
35=4
15=5
(38)
7=92
7=47
(40)
79=1
=627
16=5
(32)
8=01
=257
(35)
2=21
=87
64=3
9=2
(43)
25=0
7=36
(46)
6=69
2=43
(49)
Transitional
Mousterian
Amudian
(33)
80=4
8=11
(34)
=543
=239
(44)
=749
(82)
(36)
1=53
<>^5
(45)
UPPER
MOUSTERIAN
, LOWER
I 11 MOUSTERI AN
AMUDIAN
using flake dimension and platform data alone. —
See Table 4 %
125
Table 44*
Basic data for Levallois flakes from Tabun* —
In d u s tr y
Upper
M o u s te r ia n
Low er
M o u s te r ia n
T r a n s itio n a l
M o u s te r ia n
A m u d ia n
P la tf o r m
A re a
P la tfo r m
C o n c a v ity
F a c e ts
E x te r io r
S c a rs
Mean, S,D0, N*
Is o la te d
S c a rs
E x te r io r
C o n v e x it y
2=203
1=503
(66).
5=623
3=097
(69)
6=768
=0927
=1516
=2292
(62)
2=674
(69)
=1187
=0757
(53)
1=398
=827
(79)
=2179
=2619
(77)
3=223
2=296
(85)
5=035
1=619
(86)
=1258
(86)
1=514
=2096
1=121
3=889
3=487
(36)
5=027
2=477
(37)
=1505
=1520
(37)
=1850
=0802
(34)
=2440
(35)
=8877
=2761
=6369
=2380
(44)
3=449
1=324
(49)
=0879
=1592
(49)
=2623
=1006
(43)
2=311
1=794
(45)
ol4l4
(67)
=1427
=2007
=0797
(79)
(33)
(46)
126
height of the exterior, ridge along which the flake traveled as it was
being removedo
There appears to be a reduction of this ridge through
time in the sequence =,
The second question concerns whether or not the addition of
these variables helps in separating the industrieso
For this analysis,
a stepwise selection of variables (based on the maximization of
Mahalonobis1 distance between groups) eliminated two of the input
variables (exterior platform angle and thickness) because their discrim­
inating power was relatively low.
nating variables.
This left a total of ten discrimi­
The results are shown in Table 45 and Figure 25=.
It is clear from the figure that the three known groups exhibit much
more separation and, in fact, show a definite temporal progression.
The dots in Figure 25 represent cases from the Transitional industry,
and these plot approximately where they would be expected to fall,
based on their position in the stratigraphic sequence.
The absolute values of the standardized discriminant function
coefficients presented in Table 45 correspond to the relative contri­
bution of each variable in calculating the discriminant functions.
Function 1, which accounts for nearly 78% of the variability, is
affected primarily by the exterior scar variables, transverse convexity,
exterior platform edge concavity and faceting.
The variables of plat­
form thickness, platform width and platform area are the major con­
tributors of the second function, followed by flake length and width.
On the basis of these results it is possible to suggest
interpretations as the nature of the separation between the industries.
On the one hand, the dimensional attributes and the independent
127
Table V?o
Summary of results of- discriminant function analysis of
Levallois industries using Levallois flakes only0 —=
N = 145-
Standardized Discriminant Function
_____________ Coefficients_______ ___
Function 1
Function 2
Variable
.14273
-.70948
W id t h
-.23380
-96135
PT
--19707
-1.2792
PW
-.14844
-1.1722
L e n g th
P la tfo r m
A re a
-.19603
1-3315
P la tfo r m
C o n c a v ity
-.36132
-09923
--34751
o33651
-.75366
.-01933
.54549
-.18396
.40157
-95469
F a c e ts
E x te r io r
P c to
S c a rs
Is o la te d
E x te r io r
S c a rs
C o n v e x it y
Eigenvalue
Percent
Variance
1
1.648
77=89
2
00
22.11
Function
□
UPPER
MOUSTERIAN
LOWER
MOUSTERIAN
Figure 25.
Populations of Amudian, Lower Mousterian, and Upper Mousterian
Levallois flakes plotted according to their discriminant scores
using additional data that reflects knapping strategy. — See
text and Table 44. The dots represent individual flakes from the
Transitional Mousterian that were not included in the computation
of the discriminant coefficients.
variables that control them are not very effective for discrimination.
As was said earlier, exterior platform angle and thickness were dropped
from the analysis because of their weak discriminating power0
Although
platform thickness and width and flake length and width were included,
they contribute most heavily to the variability along the second
discriminate function, which is accounting for only 22# of the vari­
ability.
This goes along with the findings presented in Figure 24.
What do segregate between the industries, however, are the variables
which reflect particular strategies for controlling the independent
variables, namely the production of a concave platform edge and facet­
ing.
We know from the analyses presented earlier in this chapter what
these variables mean in terms of their effects on other aspects of the
flakes.
But in a multivariate comparison of these industries it is
evident that considerations of the strategies are, in this case, more
important than a consideration of the final result.
The number of exterior scars, the percentage of isolated scars,
and the transverse convexity are also among the most important vari­
ables in this comparison.
These variables all relate to aspects of
(
core surface preparation.
The fact that the transverse convexity
decreases through time may reflect a developing ability to control the
direction of flake removal through means other than a high ridge.
Certainly there is an increase in the number of scars through time, and
this probably relates also to more complex core preparation.
All of
these variables will have to be analyzed more fully in order to better
understand their meaning.
It is suggested, however, that these
variables of exterior flake morphology probably do not represent
130
intended end-results0
It is unlikely, given the nature of the flint-
knapping process, that the actual number of flake scars is of any
importance to the knapper„
It is more likely that the changes in core
preparation reflect changes in strategy that may have occurred inde­
pendently of other strategies evidenced in platform preparation*
It is also possible to suggest interpretations regarding the
relationships between these industries*
Figure 25 suggests a unidirec­
tional trend among these industries and the same is true for the
individual discriminating variables*
This, then, suggests a strong
continuity in development that is not apparent in the typological
description of these industries*
This study shows the importance of examining many aspects of
variability when making industrial comparisons*
It also demonstrates
the relative importance of particular aspects of that variability*
In this case, some of the strategies employed by the Tabun knappers
are more clearly distinguished than are their results*
This study has
significant implications for the refinement of temporal frameworks for
the Near Eastern Levaliois industries*
But its primary purpose here
is to illustrate the methodology of exploratory analysis in interpret­
ing assemblage variability*
At this time it is important to summarize the two analyses
presented in this chapter so that the point of each is clear*
The
first was intended to show that to a large degree, variation in flake
dimensions between major industries can be explained on the basis of
certain kinds of preparation evidenced on the platforms*
To some
extent this was foreshadowed by the multiple cprrelations performed
131
in Chapter 3 which demonstrated the relationships between flake dimen­
sions and certain independent variables of the platforms
But what
should be clear from this analysis is that it is possible for knappers
to control, and overcome, some of these relationships in order to obtain
particular resuitso
This was the case in the Mousterian industries,
whereby using the technique of platform dipping thinner, and ultimately
wider, flakes could be produced*
Thus, the point here is that through
an examination of the independent variables specific strategies used by
the prehistoric flintknappers to obtain particular results can be
discovered and understood in a completely objective and quantifiable
fashions
The second analysis, an exploratory analysis, was designed to
compare the Tabun Levallois industries in terms of overall technologic,al variabilityo
Several variables were added to the analysis in­
cluding some that reflect aspects of exterior flake morphology*
It
was found that differences in strategy account for most of the vari­
ability among these industrieso
These results do not lessen the
importance of dimensional variability for assemblage comparisons*
Instead, they show this kind of variability in the context of other
strategies employed in lithic production for these particular assem­
blages*
The fact that the observed differences in strategy are gradual
and unidirectional suggests an industrial continuity in the Tabun
sequence that is not observable in the typology*
This is, however, an
hypothesis generated on the basis of this one exploratory analysis*
Further work will be necessary to clarify the meaning of the variables
of exterior flake morphology and to see if this sequence holds for
other collections,.
CHAPTER 5
SUMMARY AND CONCLUSIONS
Because chipped stone artifacts constitute the overwhelming
bulk of our evidence of human activity prior to the appearance of
settled village life, the evidence derived from the study of chipped
stone artifacts is of great importance for the interpretation of man's
early development0
It has been emphasized here that there is still
considerable work to be done regarding our understanding of that
evidenceo
Above all, the interpretation of stone artifacts requires a
knowledge of the factors and processes that give rise to their mor­
phological variabilityo
The purpose of this dissertation has been to
demonstrate some particular cause-and-effeet relationships that are
basic to the development of this knowledge=
In Chapter 1 it was emphasized that there are four major fac­
tors that contribute to lithic formal variability«
materials, technology, function and styleo
morphology are both direct and indirecto
These are raw
Their effects on lithic
For example, Chapter 4
presented an example in which differences in dimensional attributes of
various Tabun industries were explained on the basis of differences in
platform preparation*
In this case it is clear that the variation in
form was due to variation in specific aspects of flintknapping
strategies in the technology of flake manufacture* A question that
was not addressed was why these strategies changed through time*
133
This
134
second question exists on a different level from the first0 The first
level is concerned with the discovery and description of those factors
that give rise to lithic variability«
was on the role of technology=
In this dissertation the focus
The second level is concerned with the
factors that give rise to behavioral variability, for example, why a
particular technological strategy was employed*
directly affects artifact form*
The latter only in­
In explaining lithic variability we
must first examine its direct causes before it is possible to examine
the factors that directed these changes*
For purposes of analysis and description, it can be argued that
technology itself exists on several levels*
For example, on a very
general level it is possible to contrast biface technology with blade
technology, each of which leads to quite different results*
Within
any one of these general technologies it is possible to identify more
specific techniques, or strategies*
For example, the use of a soft
hammer versus a hard hammer in biface production represents a differ­
ence in strategy, as does the production of concave exterior platform
edges in the later Near Eastern Levallois industries*
On a still more
specific level are the relationships that exist in the actual mechanics
of flake production*
Chapter 3*
This is the level of technology examined in
Beyond this is the level of explanation of the physical
mechanics of these relationships, although such explanations were not
attempted here (see Faulkner 1972; Speth 1972, 1974)o
It could be argued that technology is ultimately responsible
for all differences in artifact form and therefore should be separated
from considerations of other factors such as function or style * This
135
conclusion is not entirely correct.
It is true that virtually all
aspects of chipped stone morphology are the result of technological
relationships existing within the framework of fracture mechanics.
However, within the general level of technological differences, con­
siderations of raw materials, function, and style still play an im­
portant role in determining final artifact form.
Pressure-flaked projectile points provide a useful example in
this regard.
These artifacts show considerable variation in form
throughout later periods in the New and. Old World in spite of simi­
larities due to technology (i.e., pressure-flaking). Some of these
formal differences are the result of differences in function (large
spear and dart points versus smaller arrowheads, for instance), and it
seems clear that many more are the result of differences in style.
Differences in raw material also play a role since some locally avail­
able materials may not be as appropriate for pressure-flaking
techniques.
Therefore, since technology is constant, the formal
differences in these artifacts must be explained largely on -the basis
of these other factors.
The same may also be true for the many
varieties of bifaces and perhaps even Levallois flakes.
All of the
factors, that is raw materials, technology, function and style, inter­
act in the production of any lithic assemblage. The point here is
that the effects of differences in technology must be controlled
before the effects of other factors can be isolated.
The evidence that provided the basis for this study came pri­
marily from two sources;
controlled experiment, in which several
variables could be isolated and their effects on other aspects of
136
lithic morphology made more clear; and statistical analysis of archae­
ological collections derived from the Tabun Cave,
Controlled experi­
ments provide an important means of analyzing particular aspects of
technological variation*
It is generally assumed that many of the
technological relationships involved in lithic production are highly
deterministic and therefore predictive*
However, the number of vari­
ables involved makes the discovery of these relationships extremely
difficult unless most of them can be controlled or held constant*
Controlled experiments allow for this and at the same time enable such
relationships to be expressed objectively and quantifiably.
The controlled experiments performed by Dibble and Whittaker
(in press), showed that there are a number of independent variables
that directly affect certain aspects of flake form*
Although all of
these independent variables act in conjunction with one another, it was
demonstrated that primarily, exterior platform angle and platform thick­
ness together determine flake dimension*
In Chapter 3 it was demon­
strated that these relationships also exist in the Tabun material with
the additional finding that platform width was largely responsible for
variation in flake width*
However, in analyzing the Tabun material it
was difficult to control for the effects of several other independent
variables such as force, material, and exterior core morphology*
For
this reason some of the relationships appeared to be less strong,
although they remain highly significant*
By u t i l i z i n g
e x p e r im e n ts a n d t h e
it
w as p o s s ib le
to
b o th
s o u rc e s
s ta tis tic a l
o ffs e t
o f e v id e n c e ,
a n a ly s is
some o f t h e
o f th e
i*e *,
th e
c o n tr o lle d
a r t if a c t u a l m a te r ia l,
d e fic ie n c ie s
in h e r e n t
to
one o r
137
the other of these methods*
Thus, controlled experiments, although
capable of quantifying highly complex relationships, are inherently
artificial*
By comparing the Tabun material with the results of the
controlled experiments it was possible to see whether the artificiality
of the latter affected or biased our understanding of the relationships
under study*
The comparison showed that this was not the case*
On the
other hand, the results of the controlled experiments made is possible
to isolate relationships in the artifactual material that might other­
wise have been too weak to be obvious through normal exploratory
analysis*
Thus, on the basis of these analyses, it was possible to isolate
several true independent variables affecting particular aspects of flake
morphology*
Independent variables sire those that are controlled
directly by the knapper and thus demonstrate the kinds of preparation
that was carried out for the production of a particular result*
dependent variables reflect these results*
The
Through statistical analysis
of the Tabun materials it was then found that there are several ways to
control these independent variables in the course of flake manufacture*
For example, the exterior platform angle can be increased by the tech­
nique of platform faceting*
To some extent it is also possible to
alter some of the more normal relationships between specific independent
and dependent variables, through techniques such as the production of a
concave platform edge*
These findings enable us to identify particular
strategies used in the past to control the manufacture of stone arti­
facts*
138
As was stated in the Introduction, the primary focus of this
dissertation is on methodology.
The studies presented here are in­
tended to demonstrate the role of independent variables in flake pro­
duction,
Chapter 4 presented two examples of the kinds of information
that can be obtained if these independent variables are included in the
analysis of lithic materials.
First, it was shown that it is possible
to explain much of the variation in flake dimensions between certain
industries on the basis of the flaking strategies used by the knappers
in producing those materials.
The second example explored other
aspects of variability including particular attributes of exterior
flake morphology.
It was demonstrated that an understanding of specific
technological strategies for controlling flake manufacture is crucial
for comparing and interpreting lithic assemblages.
W h ile
to
lith ic
s e r ta tio n
of
it
to
th e
a v a r ie ty
As i s
k n o w le d g e
a re
a s p e c ts
o f e x te r io r
th ro u g h
c o n tr o lle d
to
th e
t h a t we h a v e
F ir s t,
o b s e r v a b le
c o n tro l
ty p e s .
c o re
fo rc e
and to
it
w ith in
to
fa c to rs
has been
th e
a re
th e
r o le
has
th a t
a im
of
c o n tr ib u te
th is
o f p a r tic u la r
s tu d ie s
th a t
e n a b le d u s
d is ­
a s p e c ts
e x p lo r e
to
new
d is c o v e r
s e v e r a l a p p a r e n tly
te c h ­
a s s e m b la g e s w h o s e m e a n in g o r
M o s t i m p o r t a n t am ong t h e s e
S e c o n d , m o re w o r k
d e te r m in e
o r h am m er t y p e
b e tte r
th e
case w ith
th e re
m o r p h o lo g y .
e x p e r im e n t s
of
a tta in e d
n o t y e t w e ll u n d e rs to o d .
o lo g ic a l m a t e r ia ls ,
m a t e r ia l
a ll
c o n c e r n in g
fr e q u e n tly
o f new p r o b l e m s .
effects
th a t
be u n d e rs to o d ,
p r e s e n t e v id e n c e
n o lo g ic a l v a r ia b le s
p o s s ib le
n e c e s s a ry
v a r ia b ility
te c h n o lo g y .
g ro u n d ,
is
assess
in
th e
w h e th e r
th e
it
s h o u ld be don e
w ill
a n a ly s is
effects
of
a re
e v e r be
o f a rc h a e ­
d iffe r e n t
ra w
139
Beyond these new areas, it will be necessary for archaeologists
to continue to use some of the other methods outlined in Chapter 1 to
discover the meaning of other aspects of lithic variability0 Two of
those methods, controlled experiment and statistical exploratory analy­
sis, were used in the present study, but undoubtedly there are still
things to be learned through ethnoarchaeology and much that can be
derived from replicative experiments0
Through such studies it will
eventually be possible to achieve a better understanding of the sig­
nificance of variability in those lithic remains that provide our only
source of knowledge of human behavior during vast intervals in the paste
APPENDIX I
GLOSSARY OF METRIC AND NON-METRIC OBSERVATIONS
This appendix defines the metric and non-metric observations
presented in this dissertation0
Flake Dimension
The dimensions of length, width and thickness were recorded on
complete flakes using the system described by Jelinek.
In Figure 1-1,
length is the measurement from A to B, from the point of percussion to
the most distal point on the flake» Width (C to D) is measured at the
midpoint of the length axis and is perpendicular to that axis0 Thick­
ness (E to F) is measured at the intersection of the length and width
axe So
Platform Measurements
Exterior platform angle is the angle at which the platform sur­
face intersects the exterior surface of a flake (the angle ABC in
Figure 1-2)=
In the controlled experiment this angle was measured with
a goniometer, with an accuracy of about 3 degrees (see Dibble and
Bernard 1980)0 However, irregularities on the exterior surfaces of
prehistoric flakes make this measurement nearly impossible with a gonio­
meter = Therefore, for the Tabun sample the exterior platform angle was
computed trigonometrically after taking three other measurements of the
140
Figure 1-1.
Schematic drawing of flake. — Top, looking down on the
exterior surface (platform surface down) illustrating
measurement of length and width. Bottom, transverse
section along width axis illustrating measurement of
thickness and exterior ridge height.
142
B
Figure 1-2.
Schematic drawing of flake (sagital section) illustrating
measurement of exterior and interior platform angle.
’
platformo
Referring to Figure 1-2, these measurements are:
143
(l) from
A to C, which represents a measurement along the platform surface from
the point of percussion to the exterior edge of the platform and perpen­
dicular to the interior surface of the flake; (2) from B to C along the
exterior surface of the flake, this distance being roughly equal to the
distance from the point Of percussion to the base of the bulb on the■
interior surface; and (3) from A to C, which is, in effect, the third
side of the triangle0
These measurements were made to within one-
twentieth of a millimeter using a vernier
scaled needle-nose caliper=
Tests by the author indicate that this method has inter-observer error
of about 3 to 4 degrees with an accuracy of about 5 degrees.,
The Interior platform angle (angle BAD in Figure 1-2) was com­
puted trigonometrically in a manner analogous to that described above
for the exterior platform angle0
Platform depth is the distance from the point of percussion to
the most exterior point on the exterior edge of the platform, measured
along the platform surface and perpendicular to the interior surface
(A to B in Figure 1-3)°
Platform thickness (A to C in Figure 1-3) was measured from the
point of percussion to the exterior surface of the flake, and is perpen­
dicular to the exterior surface0
In other words, it is the thickness
of the flake measured at the point of percussion.,
Platform width (Figure 1-4) is simply a width measurement taken
at the juncture of the platform surface and the flake edge0 Those
flakes whose interior surface intersected a lateral edge of the core
were ignored because this juncture could not be defined.
144
B
Figure I-3*
Schematic drawing of flake (sagital section) illustrating
measurement of platform thickness and platform depth.
145
Platform
Figure 1-4.
Width
Schematic drawing of flake (viewed toward platform surface)
illustrating measurement of platform width.
146
Exterior platform edge shape, as a nominal variable, was ob­
served by viewing the platform from above the platform surface (see Fig*
21)„
If any portion of the exterior platform edge was concave the
platform was considered to be concave0
The continuous measure used in
Chapter 4 was computed on the basis of two measurements=
If the plat­
form was convex, the shape was equal to the platform depth divided by
the platform widtho
For concave platforms, the shape was equal to the
depth of the dip (A to B in Figure 1-5) divided by platform width and
multiplied by minus one.
Thus, concave platforms have negative values
and convex platforms have positive values for platform edge shape„
Other Observations and Measurements
Exterior convexity of the flake is an index computed by dividing
the maximum flake thickness at the midpoint of the length axis (G to H
in Figure 1-1) by flake widtho
In effect it represents the height of
the ridge along which the flake traveled as it was removed from the
core0
Exterior flake scars were counted as they appeared on the ex­
terior surface of the flakeo
Isolated flake scars are those older
scars that have been almost, but not entirely, obliterated by subse­
quent flakingo
To be coded as isolated, the flake scar should not
intersect the edge of the flake0
Platform facets were simply counted as they appeared on the
platform surface.
To be counted, the facet must have originated from
the exterior edge of the platform and continued to the interior edge
of the platformo
14?
Figure I-5»
Schematic drawing of flake (viewed toward nlatform surface)
illustrating measurement of concavity of exterior platform
edge shape.
148
Termination was observed on the distal end of the flake0 For
purposes of this study three categories of termination were recorded*
Referring to Figure 1=69 feather terminations (A) are characterized by
sharp distal edges, while hinge terminations (B) have rounded distal
edgeso
Overshot flakes (C) have evidence of the core edge or end of
the nodule on the distal edge*
149
Figure 1-6.
Schematic drawing of flake with (A) feather, (B) hinge,
and (C) overshot terminations.
APPENDIX II
METRIC AND NON-METRIC OBSERVATIONS
150
151
Table II-10 Raw data listing of Tabun samples for non-metric variables.
— NAME (UM=Upper Mousterian, LM=Lower Mousterian, AM=
Amudian, UY=Upper Yabrudian, LY=Lower Yabrudian, AC=
Acheulian, XIV=Unit XIV Bed 90E); INVEN (l=retouched tool,
2=complete flake, 3=broken flake); SCAR (number of exterior
flake scars); ISCAR (number of isolated flake scars);
TERM (l=feather, 2=hinge, 3=distally overshot core, 4=
distally overshot nodule, 5=laterally overshot core, 6=
laterally overshot nodule); FACET (number of platform
facets); DIP (l=concave exterior platform edge; O=convex
exterior platform edge); EXT. RIDGE (maximum mid-transverse
flake thickness divided by flake width)o
NAME
INVEN
SCAR
2
3
1
2
2
2
0
2
1
2
I
2
2
2
1
1
2
1
1
3
1
3
1
2
3
2
1
2
6
9
0
8
4
9
3
3
10
5
8
8
10
14
3
5
8
3
5
6
4
5
8
5
7
ISCAR
TERM
FACET
DIP
3
2
5
8
10
6
3
3
5
1
6
7
11
6
0
9
6
5
5
6
0
1
8
2
2
2
8
1
1
1
0
1
1
0
0
0
0
0
0
1
1
1
0
1
1
0
0
0
0
1
1
1
1
0
0
0
EXTo
RIDC
i.
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
5
6
2
0
3
0
1
0
1
1
0
5
1
0
>2
0
3
0
1
1
0
0
1
0
0
1
1
0
0
0
0
i
1
1
1
1
1
1
3
1
1
6
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
-
0o 161
0 o 15 4
0o088
0.065
0.074
0,133
0.000
0.118
0.000
0,133
0.071
0.071
0. 086
0.074
0.137
0. 000
0.143
0.000
0.000
0.125
0.156
0,000
0 .000
0 .000
0.146
0.229
0.000
0.000
152
Table II-1— Continued
NAME
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UN
UM
UM
UM
UM
UM
UM
UM .
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
INVEN . SCAR
2
3
1
2
3
2
2
2
2
3
2
3
2
2
3
1
2
2
3
2
2
1
2
3
2
2
1
1
2
2
2
1
2
2
1
2
2
1
2
1
1
2
2
3
10
8
7
8
8
6
6
4
13
7
9
5
3
5
0
6
5
0
11
3
6
7
6
7
5
4
5
2
7
5
0
1
6
0
5
11
7
3
5
4
1
4
Raw data listing of Tabun samples for non­
metric variableso
1SCAR
0
1
0
1
2
2
1
1
0
3
0
2
0
0
0
0
0
0
0
2
0
0
0
1
2
0
0
0
0
0
1
0
0
0
0
0
2
0
0
1
1
0
0
TERM
1
1
1
0
2
3
1
1
1
1
2
1
1
1
0
1
4
1
1
1
1
2
2
1
1
1
4
1
5
6
i
i
i
6
1
1
1
1
1
3
1
1
4
FACET
5
7
5
2
• 7
6
4
6
3
QJ
1
0
2
0
10
9
1
1
8
10
2
5
5
6
8
5
6
3
2
5
12
7
3
8
9
0
4
17
7
3
1
1
2
DIP EXT.
0
0
1
0
0
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
1
0
0
1
0
0
0
0
1
1
1
0
0
1
1
1
1
0
0
0
0
0
RIDC
0.000
0.200
0.103
0.149
0.000
0.306
0.000
0.143
0.000
0.0?8
0.000
0.194
0.147
0.222
0.115
0.000
0.405
0.222
0. 000
0.000
0.095
0.000
0.135
0. 000
0.135
0.061
0.000
0.129
0.140
0.294
0.229
0.000
0.250
0.133
0.000
0.000
0.000
0.000
0.167
0. 157
0.200
0.242
0.145
153
Table II-l— Continued. Raw data listing of Tabun samples for non­
metric variableso
NAME
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
INVEN
SC AR
ISC AR
2
3
2
2
3
3
2
1
3
2
2
2
2
2
1
2
3
2
3
3
2
2
2
2
3
2
2
3
2
2
2
2
2
1
2
2
1
2
2
1
3
2
2
5
11
3
2
4
5
16
4
5
4
1
4
6
7
7
3
6
6
4
7
8
6
4
3
0
6
6
3
3
9
0
6
4
4
2
4
2
4
10
6
5
1
4
0
3
0
0
0
0
1
0
1
0
0
2
0
0
2
0
0
0
0
0
1
0
0
1
0
0
2
0
0
0
0
2
0
1
0
0
0
0
2
1
0
0
0
,
TERM
-
1
1
2
1
1
1
1
1
3
1
1
4
5
1
1
1
1
I
1
1
3
3
1
1
1
5
4
0
0
2
2
2
5
1
1
5
1
1
1
1
3
2
1
FACET
1
8
5
1
9
2
7
5
1
2
1
1
5
5
1
2
5
6
1
9
7
1
2
2
1
O’
2
6
0
3
1
3
4
0
8
5
1
4
3
1
7
5
3
DIP EXTo RID<
.
0
0
0
1
0
1
0
0
0
1
0
0
0
0
0
0
1
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
Oo 214
0 o 167
0 o 379
OoOOO
0 = 156
Oo 341
0= 074
OoOOO
OoOOO
OoOOO
Oo 238
0 o220
Oo 216
0 o 104
0 o 371
Oo 063
Oo 175
Oo 091
Oo 174
0 o056
Oo 057
Oo 250
Oo 118
0*158
0 o091
boiii
0,278
0,194
Oo 169
0 o233
Oo 125
0 o 122
0,000
0 o 145
0 o684
0 o192
Oo 356
Oo 172
0 o067
0 o313
Oo 286
Oo 167
Oo 147
154
Table II-l— Continued
NAME
UM
UM
UM
UM
UM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
Raw data listing of Tabun samples for non­
metric variableso
INVEN
SCAR
ISCAR
1
3
3
2
2
2
2
1
1
3
1
3
1
3
2
2
2
1
3
1
1
2
2
1
2
1
2
1
2
2
1
2
2
3
2
2
3
2
1
2
2
2
2
0
6
6
4
4
3
5
2
3
10
5
5
3
2
6
3
3
5
7
4
4
6
6
1
3
5
3
3
7
8
2
4
5
3
3
5
5
5
5
6
4
6
5
0
0
1
0
0
0
1
0
0
2
2
1
0
0
2
0
0
1
2
1
1
1
1
0
0
1
0
0
2
1
0
1
1
0
0
0
2
0
1
1
1
1
1
-
TERM
6
1
1
0
1
4
1
6
1
1
1
0
1
2
2
4
4
1
3
1
1
1
1
6
1
1
2
1
2
1
6
1
1
1
5
1
3
3
1
1
1
1
1
FACET
0
12
2
6
8
3
2
5
2
1
1
5
1
6
9
2
2
0
3
7
0
7
1
1
1
1
5
7
1
2
1
2
2
1
3
8
4
6
1
5
1
2
1
DIP
0
1
1
1
1
0
0
1
1
0
0
1
0
1
■ 0
0
0
0
0
1
0
1
0
0
0
0
0
1
0
0
0
0
0
0
1
1
0
0
0
0
0
1
1
EXTo
RIDI
OoOOO
0 o 241
OolOO
Oo 394
0 o 148
0 o 263
Oo 190
Oo 185
0 o 370
OoOOO
0 o 211
0 o 241
0 o 172
0 o33 3
0 o 29 2
0 o 040
Oo 2 73
0 o 192
Oo 303
0 o 143
OoOOO
Oo 222
Oo 304
Oo 206
0 o 412
0 o 133
Oo 107
Oo 103
0 o 133
Oo 067
Oo 286
Oo 386
0 o 167
Oo 500
0 o 143
Oo 273
0 o 13 6
Oo 310
0 o 286
Oo 192
0 o2 5 0
Oo 125
Oo 079
155
Table II-l— Continued
NAME
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
Raw data listing of Tabun samples for non­
metric variables*
INVEN
SCAR
XSCAR
TERM
FACET
1
2
2
2
1
2
2
1
I
2
3
2
I
X
2
X
2
3
2
2
2
0
2
3
2
X
1
2
3
2
2
2
X
2
2
3
2
2
3
X
X
X
3
7
5
5
6
5
6
4
7
5
7
7
6
4
5
6
4
5
0
4
4
4
3
'2
6
2
4
4
4
2
3
3
4
5
4
6
3
5
5
4
7
7
3
6
2
1
X
X
X
1
0
X
0
2
2
X
0
0
0
1
2
0
1
0
0
0
0
X
0
1
0
0
0
0
0
0
X
0
2
0
1
X
0
2
2
0
0
1
4
1
6
X
X
X
0
4
1
X
1
4
X
6
1
4
0
X
X
1
X
1
X
0
0
: i
1 2
6
1
X
4
1
1
1
1
2
X
1
1
X
1
1
4
X
4
3
2
4
5
X2
2
2
3
4
X
6
2
X
4
3
1
5
4
2
X
3
X
1
3
1
X
5
2
11
2
1
1
1
1
3
3
0
4
4
2
DIP EXT* RIDE
0
0
0
0
1
1
0
0
0
0
1
0
0
1
0
0
0
0
0
1
1
0
0
1
0
0
0
I
0
1
1
1
0
0
0
0
0
1
0
0
0
0
0
0 *400
Oo 000
0 o261
Oo 300
0.263
Oo 100
0 o238
0 oX51
Oo 182
0.148
0.127
0.093
0.292
0.182
0.1X8
0.217
0.174
0.000
0 o148
0.095
0 =250
0.261
0.216
0.185
0.214
0.355
0.186
0.170
0.147
0.231
0.188
0.214
0.227
0.000
0.200
0. 182
0.321
0.267
0.000
0. 350
0.118
0.167
0.300
156
Table II-l— Continued
Raw data listing of Tabun samples for nonmetric variables*
NAME
XNVEN
SCAR
ISCAR
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM .
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
TR
TR
TR
TR
TR
2
1
1
2
1
2
1
2
1
2
2
3
3
2
3
2
1
2
1
2
2
2
0
2
2
3
1
3
1
1
2
2
1
1
2
2
3
2
0
2
1
3
1
5
5
11
4
4
3
4
3
0
5
7
3
3
0
5
3
4
8
3
6
5
5
4
4
8
2
3
5
3
3
7
2
0
4
4
5
4
4
1
5
0
0
6
1
0
4
0
0
0
0
0
0
0
2
0
0
0
1
0
1
2
0
2
1
0
0
1
2
0
0
0
0
0
2
0
0
1
0
1
0
1
0
1
0
0
2
TERM
1
1
1
1
1
2
1
4
1
1
1
1
5
6
1
1
1
1
1
4
1
1
1
1
2
1
1
1
1
5
1
2
0
1
.1
1
2
1
2
4
1
1
5
FACET
DIP
4
5
1
1
1
2
5
1
1
6
1
7
2
1
2
1
3
5
1
5
1
6
7
1
4
1
6
1
2
1
3
3
3
5
9
7
3
4
1
1
0
10
1
0
0
1
0
0
0
1
0
0
1
1
0
0
1
1
0
0
1
1
0
0
1
1
1
0
1
1
0
1
0
0
0
0
0
1
0
0
0
1
1
0
1
0
,
.
EXTo
RID(
0 o 091
OoOOO
0 o 273
Oo 125
0 o 235
0 = 250
0=167
0 = 217
0 = 000
0= 103
0=217
0= 148
0 = 000
0 = 300
0 = 143
0=143
0 =200
0=250
0 = 000
0= 125
0 = 150
0 = 143
0 = 100
0 = 217
0 =194
0=143
0 = 000
0=286
0 = 143
0 =429
0 = 171
0=227
0=000
0 = 185
0=114
0 = 344
0 = 080
0 = 105
0 = 000
0 = 143
0=000
0 = 000
0 = 000
157
Table II-l— Continued
NAME
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
INVEN
1
3
2
2
2
1
3
1
2
3
1
1
1
2
3
1
2
1
3
1
3
2
2
3
3
2
2
1
3
2
3
3
2
2
3
1
3
1
1
2
2
I
3
SCAR
5
7
4
6
2
0
5
4
4
4
5
0
7
0
2
2
5
0
4
0
6
3
4
5
3
3
5
0
3
5
2
5
5
2
5
1
2
0
1
2
5
0
0
Raw data listing of Tabun samples for non­
metric variables.,
ISCAR
TERM
1
2
0
2
0
0
2
2
0
0
2
0
2
0
0
0
1
0
0
0
2
0
0
1
0
0
1
0
0
1
0
1
0
0
0
0
0
0
0
0
1
0
0
6
1
1
4
1
1 .
2
1
2
1
1
1
0
4
2
2
1
1
1
6
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
6
6
1
1
6
6
' 1
0
FACET
1
1
4
0
2
5
1
1
2
3
4
10
1
1
4
3
1
0
1
1
2
3
3
3
3
2
4
0
0
3
0
10
0
1
8
2
10
1
2
5
1
0
0
DIP EXTo RID'
0
0
1
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
1
1
0
0
0
1
0
0
1
0
0
0
0 o256
0 o240
0 o050
0.313
0.148
0.000
0.000
0.419
0.194
0.105
0.000
0.000
0.173
0.364
0 =216
0=129
0.350
0.000
0.200
0 =000
0.393
0.200
0.100
0.174
0.133
0.233
0.000
0.000
0.000
0. 100
0.000
0= 188
0.148
0.000
0.000
0.110
0.333
0.000
0.000
0.152
0.257
0.000
0 .000
158
Table II-l— •Continued
NAME
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
INVEN
SCAR
Raw data listing of Tabun samples for non­
metric variableso
ISCAR
TERM
3
4
1
0
1
1
1
0
1
2
2
2
2
2
1
1
1
0
1
0
0
7
3
1
5
0
0
0
0
0
0
4
0
1
2
16
3
0
4
8
3
5
5
3
7
1
1
2
1
2
1
2
2
1
1
2
0
2
2
0
0
1
1
2
0
0
1
0
2
0
3
0.
2
1
2
0
0
2
0
2
1
0
0
3
4
3
0
0
0
2
6
1
0
1
3
1
1
3
2
1
0
1
1
3
2
1
0
3
4
5
0
4
5
0
3
6
0
6
7
3
I
1
5
0
1
2
0
3
2
0
1
0
0
0
0
1
6
FACET
4
1
0
0
2
1
1
6
1
6
2
2
2
2
1
1
1
1
1
1
1
0
4
0
1
1
2
2
1
1
1
1
1
2
1
0
6
1
2
2
1
0
16
7
2
5
2
1
0
2
5
1
0
2
1
4
1
1
2
1
2
0
3
1
1
2
3
1
2
1
2
1
1
1
3.
3
DIP EXTo
0
0
0
0
0
1
1
0
1
0
1
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
Oo 385
Oo 000
OoOOO
0.083
0.000
0.000
0.000
0.072
0.250
0.222
0.125
0.286
0.000
0 = 286
0.136
0. 053
0.000
0.000
0.217
0.288
0.000
0.261
0.000
0.235
0.282
0.000
0.000
0 . 000
0
0
0
0
0
0
0
1
1
0
0
0
0
2
0
0
3
0
RED!
0.114
0.128
'
0.243
0.000
0.000
0.000
0.263
0.000
0.303
0.000
0.000
0.000
0.000
0.000
0.290
159
Table II-l— Continued
NAME
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
INVEN
SCAR
Raw data listing of Tabun samples for non­
metric variableso
ISCAR
TERM
FACET
2
1
1
1
1
1
1
6
8
2
3
3
0
6
1
2
6
2
0
1
6
1
1
1
9
3
4
2
1
3
4
0
0
0
1
0
1
0
1
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
2
0
1
0
0
1
0
0
1
1
1
1
1
1
2
1
1
0
1
2
1
6
1
1
1
1
1
1
1
6
0
1
1
1
2
1
X
3
2
2
1
2
2
2
2
3
4
1
4
3
5
5
3
3
1
1
3
5
4
3
1
0
0
0
3
3
0
1
1
1
1
0
1
1
1
2
1
0
0
3
2
1
1
1
2
1
2
2
2
2
3
3
2
1
3
0
2
7
3
2
2
5
2
2
5
1
5
3
4
5
1
4
0
0
0
1
0
0
0
0
•
5
3
6
5
2
X
5
2
X
0
3
XO
4
2
6
0
2
0
X
0
1
X
5
X
0
X
X
4
X
X
5
X
0
X
2
X
X
6
1
2
2
DIP EXTo RXDC
0
1
0
0
Ooxeo
Oo 2 33
0.167
X
X
OoOOO
0.145
0.172
0
0
0
0
0
0
0
0.000
0.000
0.052
0.061
0.000
0 .172
0.000
X
0.065
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
0
0.000
0.000
X
0.128
0.333
0.000
0.160
0.106
0.000
0.000
0.000
. 0.000
0.000
0.000
0.225
0.000
0.214
0.200
0 . 444
0.314
0.000
0.000
0.143
0.270
0.259
0 =286
0.195
0 . 200
0.571
0 .2 X6
l6o
Table II-l— Continued
NAME
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
INVEN
3
2
1
1
1
1
2
SCAR
6
6
0
I
2
2
3
3
5
1
2
1
1
0
2
2
0
3
4
1
1
0
3
8
0
0
0
2
1
1
1
1
1
1
2
2
2
1
2
1
1
1
1
2
1
1
2
2
1
3
3
3
2
3
2
0
0
3
3
2
2
2
1
2
1
3
1
1
3
3
3
4
4
3
1
2
1
3
2
Raw data listing of Tabun samples for non­
metric variableso
ISCAR
2
0
0
0
0
0
0
1
0
0
0
0
2
0
0
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
TERM
6
2
0
0
1
1
1
6
0
5
5
1
4
0
1
1
1
0
0
1
1
6
1
6
1
1
1
0
4
4
6
6
1
6
6
2
1
2
1
1
4
1
1
FACET
1
2
1
2
DIP EXTo
1
2
0
1
1
0
0
1
1
0
0
0
0
0
0
0
1
0
0
1
0
1
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
3
X)
4
2
1
1
2
1
1
1
1
2
4
1
1
2
0
4
1
2
1
2
1
1
2
1
6
2
1
1
1
1
4
0
1
1
6
4
RIDI
0 o 200
0 o0 87
Oo 000
Oo 127
0 o 167
OoOOO
Oo 385
0 o452
OoOOO
0 o3 3 3
0 o 222
0 o267
0 o 325
0 o 179
0 o2 4 5
0 o 231
0 o 4 44
OoOOO
OoOOO
0 o200
0 o 261
0 o290
0 o 489
0 o 189
OoOOO
OoOOO
0 o 255
0 o235
Oo 185
0 o385
OoOOO
0 o 500
0 o2 5 6
0o500
Oo 204
0 o 286
Oo 294
Go 100
Oo 167
Oo 211
0 o172
0 o318
0*154
161
Table II-l— Continued
SCAR
NAME
XNVEN
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM 1
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
2
2
2
3
1
1
1
1
1
1
2
1
1
5
3
3
3
3
2
1
1
1
1
2
1
1
2
2
2
2
2
2
2
2
3
3
0
1
0
0
0
0
2
3
1
1
2
2
2
5
2
1
3
1
3
4
2
2
6
4
5
0
3
1
2
0
3
2
2
3
3
4
6
0
2
2
0
3
5
4
2
2
6
5
4
3
Raw data listing of Tabun samples for non­
metric variables*
ISCAR
0
1
0
1
1
0
1
0
0
0
0
0
0
0
0
2
1
2
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
2
1
0
0
1
2
0
0
TERM
1
2
0
1
6
1
6
1
6
1
1
0
4
2
2
6
4
4
0
0
1
1
2
6
1
6
2
6
1
5
0
1
1
3
6
3
1
6
1
1
6
1
6
FACET
1
1
1
2
5
1
3
1
2
3
1
1
1
3
2
8
3
3
5
2
1
2
1
5
1
1
1
4
4
3
0
0
0
2
1
2
2
0
0
3
1
2
1
DIP EXTo
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
RID!
0 o 067
Oo 167
0,269
0,208
0,222
0,217
0,583
0,000
0,300
0,222
0,541
0,188
0, 333
0,280
0,240
0,304
0,133
0,227
0,000
0,000
0,167
0,38 5
0,353
0,414
0,179
0,000
0,365
0,323
0,184
0,182
0,000
0,208
0 , 000
0,000
0,435
0,261
0,458
0,333
0,387
0,286
0 = 196
0,200
0,235
162
Table ,11-1--Continued
NAME
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
INVEN
1
3
1
0
3
1
2
1
2
2
1
2
2
1
0
2
SCAR
2
1
2
0
5
3
1
0
0
0
3
3
4
6
1
0
7
4
2
5
3
0
4
3
4
4
4
2
4
6
2
3
0
3
5
1
0
3
4
1
1
1
1
0
0
0
0
1
3
2
1
1
1
1
1
1
3
0
1
0
0
1
0
0
0
0
1
0
0
0
1
1
0
0
0
1
0
1
0
0
0
0
0
0
2
0
0
2
0
3
3
i
3
I SCAR
0
0
0
0
0
2
1
1
2
1
2
1
2
1
1
Raw data listing of Tabun samples for non- .
metric variables®
4
6
0
0
4
TERM
1
5
6
6
4
1
6
6
1
1
5
3
1
6
1
1
1
FACET
2
2
3
1
1
1
4
2
1
1
0
3
I
2
3
1
1
4
7
2
6
1
2
1
2
1
I
1
1
1
6
1
6
1
6
1
1
6
1
6
6.
2
1
5
1
6
1
1
1
1
3
5
4
3
1
1
1
2
0
1
1
1
2
1
3
2
1
0
1
DIP EXTo RiDGl
1
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
1
1
0
1
1
0
1
0
0
0
0
0
0
1
1
0
0
0
0
Oo 138
0 o114
0 o 42 3
0 o 444
Oo 571
0 o250
Oo 462
Oo 292
0 o 22 2
0 o696
0 o 2 26
Oo 423
0 o211
0 o 326
Oo 346
0 o615
Oo 116
Oo 179
Oo 173
Oo 209
0 o 375
OoOOO
Oo 313
Oo 727
0 o190
Oo 316
OoOOO
OoOOO
0 o222
OoOOO
0 o0 9 8
0 o190
0 o 377
OoOOO
OoOOO
0 o212
0 o667
OoOOO
OoOOO '
OoOOO
0 o348
OoOOO
OoOOO
163
Table II-l— Continued
NAME
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
INVEN
2
1
3
3
2
1
2
2
2
0
1
2
2
3
1
2
1
1
2
1
1
1
2
3
1
3
2
1
2
2
1
1
3
2
1
1
1
1
1
1
1
1
3
SCAR
5
5
4
2
2
1
3
2
4
2
0
3
1
2
2
3
0
0
8
4
0
0
0
0
0
10
6
5
1
2
0
2
4
1
2
0
1
0
0
1
0
6
3
Raw data listing of Tabun samples for non­
metric variableSo
ISCAR
TERM
6
1
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
0
0
0
0
0
4
5
1
0
1
6
1
1
1
1
6
1
1
1 .
1
6
1
3
2
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
'
FACET
DIP
1
1
1
1
0
0
0
0
0
0
0
0
1
1
0
1
1
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
5
2
1
1
2
1
0
0
0
0
2
2
0
3
2
2
2
1
4
3
1
0
1
2
1
1
2
1
6
2
1
2
5
2
5
1
6
6
0
4
0
5
2
2
0
8
1
2
0
1
1
2
1
1
0
1
1
1
1
1
2
0
0
0
1
1
EXTo RID!
0 o552
Oo 178
Oo 185
OoOOO
0 o 375
Oo 000
0 o2 7 3
0 o375
0 o 167
Oo 119
OoOOO
OoOOO
0 o231
Oo 205
Oo 333
0 =050
0 o262
OoOOO
0 =105
0 =000
OoOOO
0=000
0 o000
0= 139
0 =079
0=000
0 = 227
0 = 000
0 =000
0 = 233
0 = 000
0 = 000
0 =000
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
0 =000
0 =295
0 =000
0=091
0 o138
164
Table II-l— Continued
NAME
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
XNVEN
SCAR
3
0
2
0
0
2
2
1
3
3
2
1
1
1
1
1
0
1
1
1
1
3
1
2
1
1
2
3
1
2
1
1
2
I SCAR
0
0
0
0
1
0
0
1
1
0
9
4
0
0
1
0
0
0
2
8
2
0
0
0
0
0
0
0
3
0
2
3
0
1
o
3
0
0
2
0
1
1
1
1
2
1
0
1
1
1
Raw data listing of Tabun samples for non­
metric variableSo
5
3
4
1
0
0
0
3
7
2
0
1
2
1
0
2
2
2
5
3
3
4
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
2
0
0
0
1
1
0
TERM
6
1
6
1
6
1
2
1
1
1
0
2
0
0
0
0
1
6
1
6
5
4
1
1
1
4
4
6
6
1
1
1
1
1
6
FACET
1
1
1
1
1
0
0
3
2
4
y
1
1
2
1
0
1
0
2
1
1
2
4
2
2
1
1
1
4
1
1
1
1
1
1
1
4
4
1
6
1
1
1
2
1
1
2
2
3
1
3
2
DIP EXTo
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
RXD<
Oo 000
0 o 163
OoOOO
OoOOO
Oo 211
0 o 14 3
OoOOO
OoOOO
Oo 145
0 o091
OoOOO
0 o179
OoOOO
OoOOO
Ooioe
OoOOO
OoOOO
0 o435
0 o103
OoOOO
Oo 167
0 o 2 20
Oo 368
OoOOO
OoOOO
OoOOO
OoOOO
0 o132
Oo 000
Oo 319
OoOOO
OoOOO
Oo 278
OoOOO
OoOOO
OoOOO
0 o 389
0 o 30 3
0 o206
OoOOO
OoOOO
OoOOO
OoOOO
165
Table II-l— Continued
NAME
UY
UY
UY
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
XNVEN
3
0
2
0
3
3
3
0
0
0
3
3
3
3
1
3
2
2
3
3
1
3
SCAR
5
5
6
6
6
0
2
0
8
3
5
4
1
0
1
1
6
1
1
6
6
1
6
6
1
6
1
2
0
0
5
7
0
0
7
3
0
1
0
0
0
0
2
0
0
0
0
0
0
1
0
4
3
7
2
0
6
3
4
1
0
3
7
3
3
3
3
3
3
3
3
3
2
3
1
2
0
1
1
TERM
2
2
0
0
1
1
3
3
1
I SCAR
7
7
1
1
3
3
3
Raw data listing of Tabun samples for non­
metric variables*
3
3
0
0
0
0
0
0
0
0
0
7
5
2
4
3
7
5
3
7
5
3
'
0
0
1
0
2
1
1
0
1
5
6
1
4
0
2
2
1
1
1
1
1
1
1
1
1
6
1
2
1
6
5
3
1
FACET
1
1
1
1
0
5
0
1
0
10
1
2
1
10
1
2
1
1
0
1
1
0
0
0
3
0
7
3
1
2
0
0
2
2
2
0
2
3
10
10
1
3
2
DIP EXTo
0
0
0
0
0
1
0
0
0
1
0
0
I
0
0
0
0
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
1
0
1
1
0
0
0
0
0
1
0
RID!
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
0 * 000
OoOOO
OoOOO
0 o000
OoOOO
0.000
OoOOO
0.000
OoOOO
OoOOO
OoOOO
OoOOO
0.000
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
0.000
0.000
OoOOO
OoOOO
0.000
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
166
Table II-l— Continued
NAME
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
INVEN
1
2
2
1
1
2
SCAR
3
5
7
4
3
2
1
3
2
1
2
1
0
2
1
6
6
1
2
3
0
0
6
2
0
4
1
1
2
0
4
5
11
3
5
1
0
0
1
1
2
8
1
2
3
2
3
1
1
3
.3
3
3
■
0
3
3
4
0
3
1
6
2
1
0
3
0
3
4
4
4
5
0
3
5
0
1
0
1
0
0
0
7
5
4
4
5
5
3
3
1
1
1
2
2
2
0
2
1
2
2
1
2
2
3
0
1
10
0
0
0
0
1
6
0
0
1
5
A
2
1
1
1
6
6
6
6
0
0
5
0
0
0
1
6
1
0
0
5
0
0
1
1
1
6
0
1
DIP EXTo
0
■5
5
1
0
FACET
6
1
1
4
5
3
TERM
1
6
1
2
12
6
2
0
2
ISCAR
0
4
0
0
0
3
3
3
3
3
3
Raw data listing of Tabun samples for non­
metric variableso
I
5
0
0
2
1
0
0
0
0
0
0
1
1
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
5
1
2
0
1
0
2
3
2
1
3
3
2
3
0
0
3
2
1
1
3
1
1
7
4
3
0
0
0
0
0
0
1
0
0
0
RID(
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0 .000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
16?
Table II-l— Continued
Raw data listing of Tabun samples for non­
metric variables,.
NAME
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
LY
LY
LY
LY
LY
LY
INVEN
SCAR
ISCAR
3
1
2
3
3
1
1
1
1
1
1
1
3
3
2
0
0
1
1
1
1
3
3
1
1
1
1
2
1
1
3
3
2
3
2
1
0
2
1
1
1
2
1
4
0
2
11
3
2
8
4
5
0
0
5
7
6
3
9
6
0
0
0
2
3
1
3
3
0
2
10
0
4
2
6
3
1
1
3
7
7
3
5
4
4
3
1
0
0
5
0
0
2
1
1
0
0
2
2
3
0
5
2
0
0
0
0
0
0
0
1
0
0
5
0
0
0
2
1
0
0
0
3
0
0
0
2
0
0
,
TERM
1
1
4
1
6
2
5
1
5
1
1
1
1
5
1
2
0
0
4
1
6
1
1
1
1
2
5
1
1
1
3
1
5
1
1
4
1
2
5
1
6
1
6
FACET
1
2
1
2
1
2
1
4
1
0
0
2
1
1
2
3
4
1
0
1
1
2
3
0
2
0
3
1
2
2
1
1
4
1
2
1
3
2
1
1
2
2
0
DIP EXTo RID(
0
1
0
0
1
0
0
1
0
0
0
1
0
0
1
0
0
0
0
1
0
0
0
0
0
0
1
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
OoOOO
0,000
0 =000
0,000
0,000
0=000
0 =000
0 =000
0 =000
0 =000
0 =000
OoOOO
0 =000
0=000
0 =000
0= 000
0 =000
0 =000
0=000
OoOOO
0 =000
OoOOO
0=000
OoOOO
0 =000
0=000
0=000
OoOOO
0 =000
0 =000
0 =000
OoOOO
OoOOO
0 =000
OoOOO
0 =000
0 =000
Oolll
0 =220
0 =233
0=000
0 =261
0 =000
168
Table II-l— Continued
Raw data listing of Tabun samples for non­
metric variableso
NAM E
XSCAR
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
INVEN
1
3
1
2
3
1
1
1
3
1
1
1
3
X
1
X
X
3
3
1
1
1
1
X
1
1
3
X
X
X
1
2
1
2
X
0
X
X
X
1
1
X
X
SCAR
2
3
X
2
4
3
0
4
2
0
2
4
7
0
0
6
0
3
5
0
0
5
3
X
X
0
5
0
3
4
0
5
0
3
0
0
4
5
2
4
3
6
0
0
0
0
0
1
0
0
0
0
0
4
X
3
0
0
3
0
0
2
0
0
2
1
0
0
0
2
0
1
X
0
1
0
0
0
0
2
1
0
X
2
3
0
TERM
6
5
6
2
2
6
0
X
2 .
X
0
2
1
6
6
6
0
X
1
6
X
4
4
X
2
6
X
X
0
2
6
4
0
6
2
2
6
2
5
X
6
4
0
FACET
1
0
X
X
X
X
2
2
3
X
2
X
X
X
0
X
0
3
2
X
X
2
3
X
0
3
X
X
3
1
X
0
2
1
0
3
0
3
X
2
X
2
X
DIP EXT. RXDi
.
0
0
0
0
0
0
0
0
X
0
0
0
0
0
0
0
0
X
0
0
0
0
X
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.577
0.351
0.000
0.143
0.158
0.367
0.243
0.115
0.258
0.171
0.000
0.162
0.000
0.000
0.000
0.200
0. 000
0.154
0.306
0.000
0.500
0.000
0.000
0.000
0.000
0.000
0.306
0.000
0.000
0.222
0.000
0.130
0.000
0.375
0.000
0.000
0.000
0.152
0.000
0.268
0.489
0.500
0.229
169
Table II-l— Continued
NAME
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
INVEN
1
3
3
3
2
3
1
1
1
3
0
0
0
0
0
3
3
1
3
3
0
0
0
2
2
2
3
3
2
1
1
1
3
3
3
1
3
2
1
3
1
1
3
SCAR
1
3
2
2
3
3
0
0
4
2
5
3
2
5
4
5
3
3
5
7
1
0
4
1
5
0
4
1
5
5
2
1
5
3
6
0
3
3
0
3
4
4
4
Raw data listing of Tabun samples for non­
metric variabledo
1 SCAR
0
0
0
0
0
0
0
0
0
0
1
0
0
1
1
0
0
2
0
1
0
0
1
0
1
0
1
0
2
2
0
0
2
0
3
0
0
0
0
0
0
0
0
TERM
2
4
1
1
4
1
0
1
1
6
1
1
6
2
1
1
5
6
1
2
6
1
2
1
1
4
1
1
2
6
1
1
1
5
6
2
1
5
5
2
4
1
5
FACET
1
1
2
2
1
2
1
2
0
2
0
1
1
3
2
2
2
1
4
0
4
1
1
1
3
1
0
3
2
2
2
1
0
4
1
1
3
3
1
0
1
1
2
DIP EXTo RID(
1
1
1
0
0
1
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
1
0
1
0
0
0
0
0 o178
0 o444
Oo 256
0 o075
0 o292
Oo 276
OoOOO
Oo 108
OoOOO
0,279
0,094
0 o222
0,227
0,000
0,000
0,300
0,250
0,000
0,159
0,071
0,243
0,265
0,136
0,263
0, 483
0,267
0,000
0,220
0,364
0, 293
0,059
0,000
0,130
0,267
0, 378
0,000
0, 179
0,313
0,000
0,106
0,262
0,171
0,154
170
Table II-l— Continued
NAME
INVEN
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY ’
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
3
3
3
2
1
2
3
2
2
2
2
3
2
3
3
2
3
2
2
2
3
2
0
0
3
3
3
1
2
3
3
1
2
2
1
1
1
2
3
3
1
2
1
SCAR
2
4
2
4
3
2
5
3
3
2
1
8
3
0
2
2
1
3
3
1
4
2
0
4
3
3
2
3
3
0
6
0
4
6
0
0
6
3
5
0
0
3
0
Raw data listing of Tabun samples for non­
metric variables,,
ISCAR
1
0
0
0
1
0
I
1
0
0
0
2
0
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
2
0
0
1
0
0
2
1
1
0
0
0
0
TERM
6
1
1
1
1
1
1
1
2
6
1
1
2
4
1
1
6
6
6
6
5
4
1
2
0
1
6
1
2
1
1
5
6
1
6
1
6
1
1
1
0
5
0
FACET
3
2
1
4
1
1
1
1
4
2
1
1
0
1
1
1
1
2
2
1
1
4
4
1
1
1
3
2
4
1
1
0
3
1
1
1
I
2
2
1
1
1
1
DIP EXTo RID(
0
1
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0 0244
0.273
0.191
0.111
0.370
0.286
0.143
0.294
0.083
0.000
0.343
0.273
0.109
0.467
0.241
0.300
0.273
0.309
0.400
0,604
0.095
0.184
0,196
0.276
0.270
0.000
0.000
0,000
0.000
0.000
0.000
0 o000
0.000
0.000
0,000
0.000
0. Ooo
0.000
0.000
0.000
0.000
0.000
0.000
171
Table II-l— Continued
NAME
INVEN
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV ■
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
3
2
3
3
2
1
1
1
3
3
1
2
1
2
I
3
2
3
1
2
1
3
3
1
2
3
3
3
1
3
2
2
1
3
1
1
3
2
1
2
3
2
2
SCAR
5
3
3
3
1
1
7
2
5
2
5
2
3
3
7
5
2
3
1
1
5
2
5
0
1
1
6
3
0
2
3
4
0
0
3
0
4
7
3
4
1
3
5
Raw data listing of Tabun samples for non­
metric variableso
ISCAR
0
0
0
0
0
0
2
0
3
0
1
0
0
0
3
2
0 '
0
0
0
0
0
1
0
0
0
3
1
0
0
0
1
0
0
0
0
1
3
0
1
0
0
0
TERM
0
6
1
1
6
6
1
1
6
2
1
2
6
5
1
5
1
1
6
1
2
0
0
6
1
1
1
1
1
6
4
6
1
1
6
6
1
1
5
6
1
6
2
FACET
1
3
1
1
2
1
1
5
4
1
1
1
10
1
1
0
0
1
I
1
4
1
2
1
1
1
1
1
1
0
1
1
1
1
3
1
0
3
2
1
2
1
1
DIP £ XT = RICH
0
1
0
0
0
0
0
0
0
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
1
OoOOO
OoOOO
OoOOO
OoOOO
0=000
OoOOO
0 =000
0 =000
OoOOO
0 =000
OoOOO
OoOOO
OoOOO
0 =000
OoOOO
Oo 000
OoOOO
OoOOO
0 =000
OoOOO
OoOOO
OoOOO
0 =000
OoOOO
0 =000
OoOOO
0 =000
OoOOO
0 =000
OoOOO
OoOOO
OoOOO
0=000
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
172
Table II-l— Continued
NAME
INVEN
SCAR
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
jXIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
2
1
3
2
2
3
3
1
1
2
1
2
2
2
2
3
2
1
2
3
2
3
3
3
2
2
2
3
1
3
6
2
1
4
9
2
1
1
5
0
2
3
5
3
0
0
0
I
6
1
2
2
3
3
3
1
3
2
2
2
1
5
0
XIV
2
2
2
2
2
4
6
4
XIV
XIV
XIV
XIV
XIV
1
Raw data listing of Tabun samples for non­
metric variables,.
ISCAR
1
1
0
0
1
5
0
0
0
1
0
0
0
2
1
0
0
0
4
1
2
2
2
1
0
0
0
0
2
0
0
0
0
0
2
0
0
0
0
0
1
0
1
1
1
0
3
0
4
2
3
I
5
0
3
9
5
TERM
1
1
2
1
1
1
2
1
6
1
6
6
5
1
6
6
5
0
1
1
6
2
2
6
2
2
I
0
1
1
1
1
1
1
1
5
0
4
FACET
1
1
1
1
1
3
1
1
1
1
1
0
1
1
1
1
I
5
1
1
2
1
1
1
3
1
2
3
1
0
2
X
2
3
1
2
X
X
1
1
6
2
1
1
0
1
1
10
.
DIP EXT.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
'0
0
0
0
0
RID<
0.000
0.000
0. 000
0. 000
0. 000
0.000
0.000
0.000
0.000
0.000
0.000
0. 000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
173
Table II-l— Continued
NAME
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
INVEN
1
3
1
1
X
X
X
3
1
3
X
2
1
1
2
2
SCAR
3
3
2
0
6
0
0
1
0
3
7
7
0
3
X
5
Raw data listing of Tabun samples for non­
metric variableso
ISCAR
0
0
0
0
3
0
0
0
0
0
1
3
0
X
0
0
TERM
X
6
6
6
5
0
0
1
1
1
1
X
1
0
6
1
FACET
X
1
2
1
2
2
X
X
0
1
X
X
X
1
X
1
DIP EXTo RIDGE
0
0
X
0
0
0
0
0
0
0
0
0
0
0
0
0
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
Go 000
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
OoOOO
174
Table II-2o
NAME
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
Raw data listing of Tabun samples for metric variables. —
NAME (UM=Upper Mousterian, LM=Lower Mousterian, AM=
Amudian, UY=Upper Yabrudian, LY=Lower Yabrudian, AC=
Acheulian, XIV=Unit XIV Bed 90E); PW (Platform width in
centimeters); PT (Platform thickness in centimeters);
LENGTH, WIDTH (in millimeters); THICK (thickness, in
millimeters); IPA (Interior platform angle, in degrees);
EPA (Exterior platform angle, in degrees)=
PW
PT
LENGTH
3o 72
lo 67
lo 95
2o 80
2o 50
2.11
2.12
1.62
2. 79
1.19
2.44
1.91
2. 75
2. 03
0o 00
2. 48
2.12
1.70
1.74
2. 53
0. 00
1.41
5. 15
3= 60
2.00
1.30
2. 50
0.70
0.84
0.38
0.64
0.48
0.43
0.60
0.77
0.70
0.70
0.73
0.65
0.54
0.67
0.62
0.00
0.54
0.55
0.55
0.91
0.64
0.00
0.40
0.94
0.8 3
0.70
0.58
0.47
0.00
42
44
41
49
46
62
53
78
58
34
56
35
55
55
62
75
68
50
74
57
44
0
0
0
97
62
77
0
WIDTH
31
26
34
31
27
30
0
34
0
30
42
28
58
27
51
0
28
0
0
32
32
0
0
0
41
35
0
0
1?4
THICK
8
4
4
3
4
6
6
9
7
6
3
3
6
4
8
7
6
5
7
6
5
0
0
0
6
7
10
0
IPA
EPA
106
0
0
125
95
90
0
90
0
87
0
0
0
0
0
0
93
0
0
122
0
0
0
0
0
0
0
0
66
85
81
75
89
89
84
75
83
73
88
77
87
84
0
78
85
87
85
54
88
0
0
0
83
74
98
0
Table II-2— Continued, Raw data listing of Tabun samples for metric
variableso
NAME
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
PW
PT
LENGTH
2= 75
2 o 80
2o 79
lo 88
4.44
3.49
2. 98
4. 28
2.05
3. 60
0.00
0. 00
1.40
0. 00
1. 96
6. 16
1.98
0.93
2. 80
4.66
1.38
4.98
4. 43
3.10
3.33
1. 86
1.63
2. 65
2 =38
3. 92
2. 65
3. 98
2.23
2. 55
2.84
5. 28
2.34
3.11
1.76
2.94
2.39
0.29
0. 00
0.44
0.60
0.71
0.75
0.84
0.82
0.64
0.56
0.00
0.00
0.00
0.00
0.66
0.00
0.58
1.43
0.28
0.32
0.52
0.96
0.77
0.89
0.63
0.64
0.90
0.12
0.79
0 =61
0.73
1.26
0.79
1.00
0.96
0.71
0.71
0.00
0.55
0.70
1.05
1.08
1.02
0.18
0.00
44
51
49
78
40
115
0
66
0
76
44
84
76
64
37
99
58
52
68
0
81
0
82
0
82
33
0
60
90
0
63
0
65
54
75
100
0
70
74
76
68
48
76
WIDTH
20
40
39
67
37
49
0
49
0
64
22
62
34
18
26
0
37
18
37
0
42
0
52
0
52
33
0
31
43
34
35
0
24
30
0
0
0
0
30
51
35
33
62
Th i c k
XPA
EPA
2
9
6
9
8
14
0
9
0
5
3
14
84
4
11
16
4
4
0
5
0
10
5
9
4
8
5
6
10
10
10
6
6
5
7,
0
5
8
8
6
8
9
0
89
0
110
0
0
0
99
0
0
0
0
95
0
104
0
0
0
89
0
0
0
110
0
0
0
0
0
0
0
0
0
0
105
0
0
0
0
92
0
0
0
0
70
75
89
80
83
92
0
87
0
0
0
0
76
0
76
84
88
0
83
0
81
91
72
91
98
67
94
84
0
85
0
83
71
82
86
88
0
93
85
67
73
0
81
Table II-2-— Continued
NAME
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
UM
PW
lo 90
3o 11
2= 69
Oo 00
OoOO
30 45
lo 44
2 o78
3o 24
3 o92
lo 08
2 o79
2o 11
lo 78
Oo 00
2 o28
3 ©67
3o 02
lo 04
20 12
4o 20
lo 75
lo 52
Oo 91
3o 59
30 83
lo 24
2o 56
OoOO
lo 28
3o 13
3o 56
1 o 54
3o 47
lo 70
OoOO
2o 17
3 o78
Oo 69
2o 25
2 o 24
3o 24
3 o 64
PT
0 o98
0 o82
1 o41
0.83
0 o95
1 o06
0.38
1.26
lo 46
lo 24
0.25
0.40
1 o05
0o8 2
0.82
0.48
1.42
0o93
0 o59
0.56
Oo 69
0 o98
0 o9 3
Oo 52
0.97
0.90
0 o39
0.47
OoOO
Oo 84
0 =47
1 o28
0 o49
1.32
0.89
0o9 2
1 o66
1 o12
0.34
0 o9 6 .
0.74
0 o86
0.89
Raw data listing of Tabun samples for metric
variables,.
LENGTH
81
76
48
50
85
63
40
92
71
0
47
55
94
61
79
51
58
67
65
44
77
63
51
29
58
107
57
0
0
132
96
55
75
109
54
50
69
40
72
43
99
45
32
WIDTH
56
30
29
0
45
41
27
0
0
0
21
41
37
48
35
32
40
44
23
36
70
44
34
19
44
81
36
36
65
43
56
41
2
55
19
26
45
29
30
32
35
30
34
THICK
13
6
5
6
7
16
2
9
13
0
1
10
7
6
12
3
8
5
4
4
6
12
6
3
7
10
9
6
17
12
10
5
6
9
11
6
18
5
3
11
10
6
6
IPA
ERA
0
111
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
95
95
0
0
0
0
102
0
0
0
0
0
0
0
0
0
100
0
0
0
0
67
77
85
86
0
84
75
85
0
71
74
91
82
0
0
77
84
93
75
87
92
79
73
70
0
82
0
0
84
107
78
0
80
82
82
94
81
90
71
75
79
80
177
Table
NAME
UM
UM
UM
UM
UM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
II-2— ^Continued
Raw data listing of Tabun samples for metric
variables,,
PW
PT
LENGTH
WIDTH
THICK
IPA
EPA
OoOO
3 o 67
3o 77
3o 89
2 o51
lo 32
lo 20
2 o46
2o 34
lo 72
Oo 42
OoOO
2o 16
3o 00
lo 94
0= 63
lo 72
lo 48
lo 85
3o 11
0= 00
3 o50
lo 98
2 o71
lo 34
lo 10
lo 63
2 o 57
Oo 50
2o 10
lo 20
lo 39
2 o72
Oo 98
OoOO
1 o79
lo 72
0 =00
lo 51
lo 33
lo 12
lo 79
1 o58
1 o30
0 =7 8
1 =08
1 o21
0 o65
Oo 54
Oo 55
0 o47
0 o71
0o80
0.24
0 o80
0 o61
3 o70
OoOO
0 o24
1 o14
0 =00
0 o61
0 o46
OoOO
0 =73
0 o71
1 o16
0 o73
Oo 3 0
Oo 52
0 o41
0 o4 2
Oo 64
0 o7 3
0o89
1 =19
Oo 48
Oo 59
0.54
0 =53
0 o77
0 =77
0 o50
0 =51
0 o48
Oo 46
73
105
27
0
71
67
85
60
81
0
53
59
69
80
96
57
71
111
126
76
86
83
61
0
70
54
31
59
55
66
86
97
57
49
51
76
62
62
89
72
63
87
57
0
29
40
33
27
19
21
27
27
0
19
29
29
42
24
25
22
26
33
28
0
36
23
68
17
15
28
29
15
30
28
44
30
8
35
22
22
29
28
26
16
~ 24
38
11
8
5
14
6
5
. 6
5
11
0
4
1
7
15
7
4
8
6
12
5
7
8
5
17
8
3
4
3
4
4
9
19
6
5
3
8
5
11
9
7
5
6
4
0
0
0
0
0
0
88
0
0
0
0
100
0
0
0
98
101
0
0
0
0
0
0
0
100
0
90
0
109
111
0
0
0
0
0
84
93
0
0
102
100
102
0
0
79
72
85
93
84
94
83
61
0
91
82
77
0
0
78
73
0
98
86
0
84
65
0
71
0
86
92
65
80
84
0
80
68
73
98
80
0
8.0
77
75
80
77
,
Table II-2— Continued
NAME
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
PW
2 o 11
lo 98
1 o 48
2o 12
2 o 88
2o 43
2o 34
4o 82
0 o 95
Oo 96
2 o63
3o 34
2o 44
2 o56
OoOO
2o 39
1 =40
lo 33
1 o 73
2= 52
lo 95
lo 19
lo 59
lo 88
lo 76
OoOO
1 o 15
4 o 27
3 o06
2o 02
lo 69
lo 31
lo 66
2o 69
2 o01
lo 23
1 o 80
3o 03
2 o.54
Oo 00
2o 31
Oo 85
2o 63
PT
1 o05
0 =31
0o70
0 o89
0 o9 8
0o73
0 p5 9
0 o89
0 =35
0o55
0 =58
1 o15
0 o6 8
0o60
OoOO
0 o77
0 =60
0 =52
Oo 73
Oo 30
0 o68
Oo65 '
1 o06
0 o60
0o93
0 o63
0 o28
Oo 7 5
1 o60
O o39
Oo 36
Oo 25
lo08
OoOO
Oo 67
Oo 58
0 o8 5
Oo 86
Oo 54
OoOO
Oo 84
Oo 50
0 o7 4
Raw data listing of Tabun samples for metric
variables,.
LENGTH
94
65
78
79
101
60
61
0
83
70
56
60
74
91
68
55
55
76
69
53
82
86
49
63
0
0
45
55
87
54
56
77
94
0
67
66
82
78
0
87
86
90
85
WIDTH
30
29
23
20
38
30
21
53
22
27
55
43
24
33
34
23
23
0
27
21
28
23
37
27
28
31
16
47
68
26
16
28
22
0
20
22
28
30
0
20
34
24
20
IPA
EPA
0
14
7
0
8
95
99
7
0
10
5
104
6
0
0
10
5
0
100
6
0
11
7
95
0
9
7
0
0
11
7
0
7
89
0
6
103
6
2
0
99
8
8
0
9
0
5
0
7
0
0
0
4
0
0
12
15
0
7
0
2
0
6
0
6
0
0
0
5
0
0
5 .
11
0
9
0
0
0
6
0
9
0
5
0
6
0
78
96
94
70
82
65
76
89
86
83
0
74
73
87
0
69
89
75
78
74
79
81
77
78
74
84
0
76
71
95
82
88
0
0
76
88
70
80
0
0
87
0
74
THICK
.
Table II-2-°Continued
NAME
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
LM
TR
TR
TR
TR
TR
PW
PT
lo 99
lo 13
2 o 38
lo 81
Oo 73
lo 42
2o 18
4 o25
3o 61
2o 93
2o 82
3o 12
Oo 00
l o 69
lo 80
1 o15
Ob 00
2o 75
2» 26
4o 00
lo 74
1 o59
3o 73
2o 11
1 o 66
lo 38
2o 84
lo 40
2 o44
1 o65
OoOO
2 o 17
2o 19
1 o 70
2o 33
3o 14
Oo 00
Oo 82
Zo 64
2 o46
Oo 00
3o 05
lo 37
0o76
0 o52
0 o98
0 o57
0 o28
Oo 77
0 o64
1 o34
0 o91
Oo 65
0o68
loOl
0 o91
loll
0 o4 0
0o56
OoOO
Oo 68
Oo 76
0 o66
0 o60
Oo 41
0 =38
0 o69
0o5 0
0 o44
Oo 71
0o79
0o71
1 o05
lo04
0o91
0 o64
0 o50
0 o65
lo23
0.95
Oo 30
0.28
0.51
0.00
0.46
0.78
Raw data listing of Tabun samples for metric
variableso
LENGTH
65
76
95
48
72
91
52
40
76
67
66
58
54
83
52
55
66
101
62
116
51
68
50
56
63
67
55
56
82
61
77
46
0
72
78
116
39
58
20
75
0
0
60
WIDTH
22
0
33
24
17
24
24
23
0
39
23
27
29
30
28
28
20
24
0
48
20
21
30
23
31
21
0
21
35
28
35
22
0
27
35
32
50
19
38
28
27
37
32
THICK
3
6
9
4
5
6
5
6
13
4
5
6
2
10
5
7
5
8
5
7
4
4
2
8
5
5
7
7
8
9
7
6
5
5
6
13
8
4
3
4
4
6
7
IPA
ERA
0
0
0
0
0
0
0
109
0
0
0
0
0
0
0
106
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
76
91
76
73
87
0
78
35
0
82
74
74
70
0
77
72
0
83
77
0
71
85
91
61
75
76
0
0
82
75
83
69
79
83
86
84
74
0
0
80
0
87
79
Table II-2— Continued
NAME
TR
IR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
PW
'
3o 21
lo 29
2 o 69
Oo 00
1.56
2. 36
1.25
1.47
1.69
4. 19
2.53
3. 04
1. 95
0 . 52
2. 92
1. 23
1. 25
2. 91
1.00
0. 52
1. 78
1.02
1.73
1. 52
2. 35
1.46
3.09
0. 00
0. 00
0. 94
0.00
2. 33
1.25
2.26
2.98
3. 08
2.22
0.00
2.96
1. 87
1.47
Oo 00
2 o46
PT
1.23
0.52
0.39
0.00
0.31
0.85
0.54
1.06
0.53
0.84
0.65
0.86
0.00
0.31
0.78
• 0.61
0.70
0.75
0.52
0.28
0.84
0.40
0.31
0.73
0.29
0.61
0.74
0.00
0.00
0.43
0.00
0.31
0.00
0.47
0.57
1.79
0.45
0.00
1.06
0.55
0.00
0.00
0.82
Raw data listing of Tabun samples for metric
variableso
LENGTH
57
62
30
73
48
0
39
68
50
79
32
98
100
76
68
49
80
31
72
76
52
76
54
0
58
91
33
0
0
57
0
79
70
32
26
63
82
68
0
64
77
0
0
WIDTH
43
25
40
16
27
0
29
43
31
38
42
0
52
22
37
31
20
40
30
0
28
15
40
23
30
30
29
0
22
30
21
32
27
30
26
73
24
0
0
33
35
0
42
THICK
8
5
5
5
4
9
7
18
9
5
6
7
11
12
8
5
8
10
5
14
9
4
5
4
5
8
10
10
6
4
7
6
5
3
7
12
7
15
11
9
9
14
6
IPA
0
0
0
0
0
0
0
0
121
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
100
118
0
0
0
95
0
0
0
0
0
0
0
0
0
0
0
0
0
ERA
66
74
72
0
83
84
77
87
82
72
87 .
77
81
0
87
81
80
0
0
0
72
77
81
80
96
57
0
0
0
84
0
0
0
70
62
79
93
0
0
87
0
0
80
Table 11=2—Continued
NAME
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
Raw data listing of Tabun samples for metric
variableso
PW
PT
LENGTH
lo 72
2 o 68
0 o 00
Bo 03
OoOO
1 o77
5 o29
2o 17
2.43
lo 40
Bo 27
lo 38
2 o 34
OoOO
lo 16
2o 30
3 o01
Oo 00
2 o45
3o 40
2 o96
2o 53
lo 71
3» 89
lo 13
2 o 18
OoOO
4o 82
1 o95
Oo 00
lo 90
2 o 25
Oo 00
2 o83
3o 03
3o 44
2o 77
2 o 16
1 o32
2o 25
2o 70
lo 22
3 o 03
0 o59
0o80
OoOO
1 o15
OoOO
0 o64
1 042
0 o48
Oo 42
0 ©72
0o46
0o56
Oo 59
0o31
0o38
0o44
1 o15
OoOO
1 o02
1 o39
1 o16
0o82
0o31
0 =89
Oo 29
0 ©34
Oo 26
1 o42
Oo 65
Oo 50
0o93
Oo 96
OoOO
0o78
1 o02
0o90
1 o24
0 o62
0 ol 7
Oo 63
Oo 40
0o30
0 =60
0
59
46
0
74
0
0
0
41
66
48
85
31
81
50
53
38
83
45
102
75
62
72
59
85
0
65
0
65
68
72
59
63
67
63
66
44
31
41
0
87
31
49
■
WIDTH
26
39
47
72
37
41
0
83
20
45
24
28
27
42
44
38
0
0
46
52
0
46
0
34
39
31
67
37
44
47
37
44
20
52
38
0
33
32
19
63
40
42
31
THICK
10
6
15
12
8
12
13
50
5
13
3
5
7
12
9
3
11
11
8
17
12
15
17
7
10
10
20
11
8
6
7
13
7
16
12
15
10
7
4
11
11
4
16
IPA
EPA
0
0
0
0
0
0
0
0
0
109
0
0
90
■
0
0
0
0
0
0
0
0
122
0
0
0
0
0
0
106
0
0
0
0
0
0
0
0
0
0
0
0
0
0
82
69
0
65
0
87
65
82
71
78
81
76
84
0
0
0
79
0
68
67
77
70
0
69
0
0
0
0
79
88
0
0
0
0
67
74
66
66
0
88
89
0
65
Table II-2— Continued
NAME
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
TR
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
'
■
PW
PT
3o 76
2.04
Xo 29
3 o 89
2.55
3. 84
2. 25
2.14
1.52
2.53
3.40
3. 07
2. 20
2. 89
1. 15
1.26
2.93
1. 56
3. 90
3. 30
3. 28
2.61
0. 00
3.15
0. 00
2.03
2. 28
2.34
1.93
0 . 00
1.94
2.04
2.00
0.00
1.27
1.55
1.93
1.49
2.13
1. 00
1.47
1.27
2.47
1.28
0.54
0.43
1.07
0.48
1.12
0.56
1.29
0.46
0.53
0.86
0.95
0.68
0.2 5
0.55
0 <j4 4
0.56
0.51
0.70
0.60
0.63
1.24
0.00
1.27
0.00
1.70
0.93
0.68
0.83
0.00
0.5 3
0.00
0.92
0.34
0.53
0.39
1.15
0.77
0.31
0.3 5
0.41
0.48
0.80
Raw data listing of Tabun samples for metric
variables=
LENGTH
73
61
78
70
34
0
64
0
44
56
37
89
62
38
58
33
77
91
30
72
68
0
0
38
101
82
50
50
92
59
74
48
71
74
86
66
68
67
49
49
47
67
55
WIDTH
50
30
30
36
33
62
29
46
58
33
26
64
39
46
0
39
39
24
38
25
47
0
0
46
96
66
37
40
0
28
25
27
35
56
0
21
37
27
21
27
20
14
37
THICK
10
6
5
12
8
11
3
21
7
4
6
12
9
5
7
4
4
9
8
5
7
12
14
10
27
23 '
11
6
7
6
6
6
11
9
3
4
19
6
6
7
4
7
8
IPA
ERA
0
0
0
0
118
0
0
0
0
0
0
0
0
72
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
96
0
0
0
63
82
82
84
77
77
75
82
0
42
63
78
79
99
84
0
0
81
68
80
0
66
0
54
0
0
76
73
69
0
80
0
68
80
85
85
76
67
0
84
62
0
0
Table II-2— Continued
NAME
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
Raw data listing of Tabun samples for metric
variableSo
PW
PT
LENGTH
2o 50
A o 27
7 o 38
3o 31
Oo 70
Oo 00
2= 38
Oo 99
5 o 56
lo 55
lo 12
2ol4
Ao 10
Ao 70
Ao 41
1.43
1 o 50
A. 28
3.63
lo 22
Oo 91
lo 99
5 o 74
lo 38
3. 79
A. 28
A o 25
I. 66
lo 14
Oo 88
3. 37
1= 52
2 o 54
lo 04
2. 44
Oo 00
1 o 54
I. 17
la 58
lo 12
lo 34
lo 60
loll
1 o06
0 o8 0
1 o8 5
1 o 67
0o 2 0
0o 70
Oo 70
0 o26
1 o79
1.02
0o55
0 o77
1 o97
OoOO
0 o77
0 o4 8
0 o8 4
1 o 08
1 o3 4
OoOO
0 o60
0o63
1 o8 4
0.52
0 o74
1 o 14
1 o62
0 o61
0 o 30
0o52
lol3
0 o68
1 o21
0.28
0 o64
OoOO
Oo 46
0 o40
Oo 48
0.42
Oo 40
0.39
Oo 30
0
29
0
0
72
49
57
91
0
48
56
79
64
0
80
67
80
0
0
65
65
51
94
45
40
31
63
0
78
53
70
66
61
63
83
58
51
82
81
54
72
61
50
WIDTH
40
46
94
71
18
0
26
31
65
27
18
60
40
67
49
39
72
0
0
20
23
31
47
37
40
62
47
17
27
13
0
30
39
18
49
21
17
60
24
19
29
22
26
THICK
12
9
17
12
4
8
11
12
17
9
4
18
19
20
12
10
36
9
16
6
8
9
22
6
10
10
12
4
5
6
13
11
11
6
7
7
5
10
4
4
8
8
5
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
76
65
54
72
0
70
78
94
0
73
73
0
70
0
82
87
■91
64
0
0
84
76
70
75
0
59
76
64
82
74
71
83
60
71
86
0
0
87
0
80
84
, 98
0
Table H-,2— Continued
NAME
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
Raw data listing of Tabun samples for metric
variableso
PW
PT
LENGTH
WIDTH
2 o69
lo 16
lo 16
Oo 86
1.69
2.40
1 o 60
0. 71
0. 91
0 o93
3.14
1.52
1 o09
2.50
lo 96
I. 99
I. 28
I. 21
4. 85
2. 13
I. 19
1 o 43
3. 48
4. 63
Oo 84
3o 37
2 o53
I. 12
I. 78
2.14
2 o79
Oo 00
Oo 00
I. 82
lo 09
I. 28
10 49
Oo 00
lo 87
1 o 45
I. 95
1 o41
1 o02
0 o34
0 o5 5
0.45
Oo 49
0 ©5 2
loOO
0 o69
Oo 38
Oo 17
0 ol 4
1 o4 4
0 o49
Oo 38
lo25
1 o22
Oo 61
Oo 53
Oo 29
1 .45
0 o91
0 o41
0 o90
1 o31
1 o20
0 o75
0 o84
0 o76
Oo 70
Oo 27
0 o77
1 o30
0.00
OoOO
0.68
0 o6 3
Oo 39
0 o34
0o68
loll
Oo 43
Oo 93
0.32
Oo 21
44
67
0
62
61
96
93
0
78
64
78
0
57
100
59
81
83
61
0
68
66
42
59
99
66
47
60
68
62
50
0
0
0
65
58
73
50
72
67
58
68
67
52
30
24
26
24
27
46
24
0
20
18
37
16
15
.50
25
23
30
22
0
0
24
13
34
29
28
25
52
31
38
33
0
24
0
0
23
23
24
18
31
28
51
20
17
THICK
2
6
8
7
6
10
12
15
6
4
14
3
.5
16
6
9
6
5
11
6
7
5
1
12
6
8
21
7
7
5
14
6
6
13
8
9
12
5
15
8
11
5
4
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
79
78
0
86
62
69
73
84
0
0
0
73
77
77
0
94
0
98
0
77
82
0
0
0
78
67
75
78
0
0
74
0
0
78
82
73
75
0
0
85
85
78
74
Table II-2— Continued
NAME
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
AM
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
Raw data listing of Tabun samples for metric
variables.
PW
PT
LENGTH
1 o56
4 o55
Oo 83
1 o59
1 o96
lo 20
lo 08
1 o 33
lo 53
0 o64
lo 60
1= 40
lo 81
l o45
lo 49
lo 68
2 o 61
2 o00
3 o12
2 o98
lo 38
1 o 31
2o 94
0 o96
3o 83
2o 01
4 o 60
3o 43
1 o 43
lo 35
3o 30
3 o19
0o 00
2o 37
3 o44
0 o93
1 o29
2o 19
4 o 10
3 o83
1 o 91
3 o 46
lo 20
0o42
1 o08
0o 4 0
0o61
0 o93
0 o42
0o95
0o52
0o63
0o 28
0o52
0o 59
0o27
0 063
0o63
0 o8 4
0 o91
0o47
1 o02
1 o09
0 o59
0 =82
1 o67
0 =89
0 o81
0o84
1 o4l
0 o54
0o47
lo31
0 o70
0o74
0o00
0 o9 4
1 o33
0 o60
0 o66
0 o56
1 o24
lo69
0o93
lo52
0o4 2
73
49
68
59
82
60
63
61
58
59
75
78
51
112
61
77
44
71
73
0
61
58
62
48
71
57
28
74
47
0
36
75
68
0
0
49
39
53
97
0
72
70
75
WIDTH
29
44
26
18
28
24
13
24
18
23
31
26
19
46
26
13
69
28
52
43
24
32
48
22
42
38
46
44
36
0
51
58
53
0
0
33
24
40
0
0
23
0
0
THICK
4
7
7
5
12
7
5
6
5
19
9
12
4
14
9
8
15
6
11
9
10
9
17
15
9
9
10
8
6
17
8
15
22
22
19
6
8
7
17
15
7
11
12
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
101
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
88
81
87
79
97
0
75
77
61
0
82
0
82
73
83
76
88
81
70
78
87
68
87
85
83
76
55
80
78
79
69
85
0
73
77
78
79
66
73
54
68
0
93
Table II-2— Continued
NAME
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
Raw data listing of Tabun samples for metric
variables®
PW
PI
LENGTH
2.47
2,42
3o 00
2o 65
2 <,57
2.19
0.92
0. 00
3. 18
3. 98
3. 65
5.50
3.47
1.05
1.20
2.53
2. 92
2. 51
1.24
3.05
4. 12
2.44
3. 05
2.50
6.87
0.00
1.45
2= 70
2.61
0.75
5. 80
4. 62
0=94
1.60
1.53
6.48
1. 13
3.04
0. 00
2.97
3.22
1.17
3. 20
1.00
0.67
0.74
1.09
1.30
1.02
0.18
0.00
1.00
0.80
1.61
1.42
0.89
0.62
0.46
0.47
0.86
0.61
1.00
0.82
0.48
1.00
0.64
0 =84
0.80
0.00
0.40
1.40
1.28
0.23
2.22
0.77
0.52
0.65
0.58
2.34
0.52
1.26
0 =66
0.84
0 =76
0.58
1.18
6
60
45
39
69
0
55
53
33
0
0
27
55
56
50
45
51
0
45
47
43
0
25
30
44
0
41
26
0
58
0
34
40
25
0
73
77
46
0
59
0
48
44
WIDTH
29
45
27
44
32
54
22
24
42
42
79
48
52
44
21
40
42
80
38
55
0
14
35
36
76
70
22
37
38
30
0
72
13
23
0
0
0
0
0
44
0
44
58
THICK
16
9
7
9
13
9
5
9
10
6
16
9
11
7
8
3
10
19
9
16
9
0
4
9
7
10
3
10
13
9
20
9
10
3
16
16
12
14
8
12
13
6
12
IPA
EPA
0
0
0
0
113
0
0
0
0
0
0
0
0
0
0
0
0
0
97
0
0
0
0
0
0
0
0
0
0
95
0
0
0
0
0
0
0
0
0
0
0
0
0
66
83
69
56
76
0
0
0
0
65
0
58
70
82
85
81
0
0
75
79
78
0
60
64
78
0
79
50
0
79
56
80
77
61
80
52
88
65
0
0
0
0
67
Table II-2— Continued
NAME
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
UY
PH
PT
5o 33
lo 84
3= 25
l o22
Oo 00
Oo 00
5o 94
2o 13
4 o 79
lo 72
Oo 72
3o 64
2o 20
3o 50
Oo 00
3 o63
2o 40
OoOO
Oo 64
4 o66
3o 85
2o 71
3o 61
2 o22
lo 65
lo 80
2o 98
6 o55
6o 62
3o 27
3 o05
2o 84
Oo 89
1 o 93
3o 59
3 o59
lo 96
Oo 46
2o 34
lo 45
lo 65
1 o 16
1 o32
0 o5 4
0 =84
Oo 90
OoOO
OoOO
1 o59
1 o3 8
1 o31
0 o40
0 o37
1 o09
lolO
0o84
0 o8 2
1 o16
1 o2 8
0 o9 8
0 o3 8
1 o59
0 o8 8
0 o9 5
0 o92
0o97
0o61
1 o44
1 o02
1 o08
1 o92
0o95
0 o98
1 o02
0o28
1 o24
2 o35
I o27
lo08
0 o21
lo02
0 079
0 o8 5
0 08 6
Raw data listing of Tabun samples for metric
variableso
LENGTH
0
59
0
82
50
70
65
39
0
0
0
85
0
0
0
0
106
57
39
69
50
56
94
33
73
75
71
84
0
98
28
0
66
0
0
55
37
102
38
63
79
60
-
WIDTH
15
43
0
0
38
28
0
49
62
55
0
56
0
0
65
83
0
46
29
0
30
41
38
24
57
0
0
53
0
47
18
0
18
61
0
0
36
33
34
24
31
24
THICK
0
6
14
16
8
4
12
13
12
8
6
13
11
19
11
17
24
15
3
15
9
11
12
11
13
15
21
8
20
15
7
12
4
19
24
12
17
8
7
9
5
7
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
101
0
73
80
69
90
0
0
75
0
66
74
0
76
81
0
0
76
0
85
0
68
62
70
71
46
88
76
85
65
0
0
48
75
81
74
73
82
77
0
58
72
59
84
188
Table II-2-— Continued
NAME
UY
UY
UY
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
Raw data listing of Tabun samples for metric
variableso
Pti
PT
LENGTH
3o 54
3o 54
1 o05
2o 83
Oo 00
3o 47
OoOO
1 o05
1= 12
4 o65
3= 02
2o 54
3o 04
0 o61
3o 19
lo 19
3o 17
1 o 80
Oo 96
lo 54
1 o 63
2.12
Oo 00
4 o64
2o 44
OoOO
3o 31
lo 60
1 =41
2= 82
0 =00
1= 43
3o 14
1= 10
2= 84
2= 14
2= 25
3= 50
1 o22
1 o05
OoOO
3 o20
1 o62
0 o4 3
0o43
Oo 40
1 o16
0 =41
0 o58
OoOO
0 o37
loOO
0o60
0 o58
0 =81
Oo 89
Oo 2 3
1 o34
0 o53
0 o50
1 =06
0 =16
0 =88
1 o26
0 o30
OoOO
1 =25
0 =96
OoOO
1 o48
0 =27
0 o30
1 o26
0 =00
0 =00
0 =92
Oo 67
0 o47
0 =00
loOB
1 o16
0 o2 9
0 o26
0 =82
0 =76
0 =62
66
66
82
0
63
0
0
57
58
59
44
64
41
40
56
51
58
74
67
37
0
47
64
0
29
43
56
59
75
61
55
0
44
78
42
51
29
44
40
89
58
69
39
WIDTH
51
51
31
0
61
42
40
28
42
51
73
33
32
32
0
32
23
38
30
27
48
27
42
0
53
39
38
33
30
35
44
38
0
45
40
30
21
32
29
27
33
35
35
THICK
16
16
4
13
6
7
4
6
18
7
10
11
6
4
15
6
4
12
4
6
10
4
9
12
11
4
14
9
12
11
21
16
12
7
10
8
11
5
7
7
5
16
5
IPA
ERA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
81
71
134
0
0
63
0
77
77
84
64
0
67
80
0
80
0
71
58
0
0
78
60
0
73
0
73
0
0
0
63
90
75
0
61
53
0
0
37
93
72
Table II-2°— Continued, Raw data listing of Tabun samples for metric
variableso
NAME
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
PW
PT
Oo 00
lo 91
lo 80
2 o 19
2o 60
2 o 72
2 o00
3 o 17
3o 17
Oo 79
3o 33
Oo 79
lo 74
2o 36
Oo 00
3o 00
2o 05
1 o47
2o 90
Oo 00
lo 87
2o 74
lo 30
0 o93
lo 94
1 o74
2o 24
lo 34
lo 54
2o 13
3o 15
lo 55
2 o03
lo 21
1 o52
1 o85
2o 51
2 o91
1 o94
3 o78
2o 13
4 o 69
1 o20
OoOO
0 o41
0 o57
Oo 85
0 o90
1 o63
0 o56
0 066
0o93
0.50
1 o29
Oo34
Oo 33
0 =72
OoOO
1 .07
0 =83
0.94
Oo 53
OoOO
lo92
1 o07
0o41
0 o36
0 o89
0 o31
Oo 64
0 o38
0.52
0 o93
1 o32
0.00
0 o41
0o28
0 .75
0o67
0 o44
1.42
0o62
Oo 76
0 o50
1 ©27
0 o36
LENGTH
61
94
42
89
30
69
0
45
0
60
61
48
50
66
59
43
58
48
38
63
75
0
32
69
60
39
100
43
39
0
32
81
48
64
61
38
82
0
0
63
59
65
0
WIDTH
32
49
40
57
34
52
38
28
0
20
50
48
38
41
34
31
19
0
37
28
30
39
30
23
48
30
63
33
24
0
33
40
26
29
40
23
64
0
0
36
24
32
34
THICK
9
7
5
13
6
18
12
12
12
9
12
10
4
8
3
6
13
7
8
9
12
15
5
5
9
8
12
5
7
18
16
14
12
6
9
6
13
16
10
4
5
12
6
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
112
0
0
0
0
0
0
0
0
0
0
0
83
66
0
61
76
82
0
80
86
76
0
53
50
0
63
76
70
74
0
69
0
88
0
85
81
89
0
65
85
62
0
92
0
77
64
0
71
75
76
79
77
76
Table II-2— Continued
Raw data listing of Tabun samples for metric
variableSo
NAME
Pti
FT
LENGTH
AC
AC
AC
AC
AC
AC .
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
AC
LY
LY
LY
LY
LY
LY
4.74
3.70
2. 15
1. 24
2.48
2 .78
0. 00
3. 05
1.53
1.50
0.00
3. 08
2. 16
3.15
3 .69
4. 16
1.63
2.10
0. 00
1.85
1.94
3. 91
1.34
2. 36
2. 00
0. 00
3. 07
0. 87
2. 37
3.77
1.42
0. 00
1.59
2= 85
5.04
1.52
1.90
6. 69
1.58
1.62
2.83
2. 80
0. 00
0.66
0.77
0.8 2
1.46
0.60
0.52
0.00
0.3 0
0.40
0.54
1.5 0
0.71
0.96
0.74
1.08
0.39
0.48
0.67
0.00
0.54
0.95
1.40
0.64
1.54
0.99
0.00
1.26
0.38
0.70
0.81
0.36
0.00
0.97
1.32
1.30
0.96
0.46
1.63
0.96
0.70
1.00
0.77
0,93
35
53
43
0
64
37
25
29
49
0
0
0
48
67
35
49
86
0
55
83
50
52
72
56
47
0
3
44
0
59
95
61
45
44
53
55
47
65
67
46
65
44
75
WIDTH
40
0
32
55
42
0
26
36
40
0
0
52
40
52
49
46
0
0
22
31
43
39
48
50
46
0
80
24
0
43
53
32
39
35
45
0
47
45
50
30
0
23
0
THICK
3
7
7
11
13
7
7
8
8
22
16
17
14
6
11
7
11
13
13
7
13
11
7
13
12
15
9
9
8
9
13
3
13
7
10
11
5
9
13
9
11
8
15
1PA
EPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
49
78
80
74
85
84
0
0
82
0
0
94
86
55
64
0
0
75
0
85
0
0
74
71
62
0
0
78
68
79
0
0
78
63
67
76
62
68
0
80
65
75
70
Table II-2— Continued
Raw data listing of Tabun samples for metric
variableSo
NAME
PH
PT
LENGTH
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY •
LY
LY
I 0I8
4.38
Oo 00
10 38
3 049
3o 58
2 0 09
5o 95
2o 31
3,38
Oo 00
3.98
3.24
2, 98
0 ,00
2,37
0 ,00
2. 44
3,22
2, 45
3,38
4.09
2 .01
1 , 88
3. 59
3= 52
2. 64
3. 78
2.49
0. 83
2.25
2. 18
4. 31
2.61
0. 00
1,50
3,58
4.41
1.46
3. 39
2.00
3 . 24
3.95
0.86
2.50
0.91
0.68
1.01
1.79
0.50
0,93
0 .66
1.20
0.00
0,84
1.42
1.95
0.88
0.84
1,38
0.59
1.44
1.95
1.30
1.22
0.66
0.80
1,36
0.51
1,36
1,13
0.82
0.33
0,98
0.90
1.68
1.19
0.00
0.50
1.06
1.60
0,89
1.30
0,00
0.78
1.91
72
72
85
46
44
0
0
70
38
43
0
70
75
0
59
75
0
50
76
0
68
62
59
50
88
69
55
0
40
44
52
67
0
58
0
74
0
70
49
55
0
61
0
WIDTH
26
57
0
28
38
49
37
52
31
41
0
74
0
0
0
35
0
26
62
0
38
0
0
0
0
0
36
0
0
18
0
54
0
32
0
0
0
46
0
41
45
28
96
THICK
12
16
16
7
10
21
12
8
7
8
11
18
12
13
11
9
17
6
21
19
20
11
8
10
19
15
13
7
13
4
14
10
0
13
0
6
11
6
10
12
17
12
27
IPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
,0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
111
0
0
0
0
0
0
0
0
0
0
0
EPA
0
0
80
67
53
76
88
68
73
59
0
77
62
59
78
66
61
71
82
61
93
58
80
74
74
0
61
61
76
75
76
71
0
71
0
85
57
68
77
71
0
80
0
Table II-2— Continued, Raw data listing of Tabun samples for metric
variableso
NAME
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
PW
PT
LENGTH
3 o94
lo44
4 o22
Oo 00
Oo 99
1 o58
3o 65
2o 70
Oo 00
Oo 00
2 o 91
lo 02
lo 06
2o 77
2o 20
2 o13
4o 51
4o 12
4o 76
lo 48
2o 83
2 o 94
2 o14
1 o48
2 o 25
3o 31
0o 00
2o 05
2o 07
2o 83
3o 51
2o 77
3o 89
0o 00
Oo 00
1o58
lo 70
Go 00
2o 99
4o 44
1 o 68
2 o 27
2o 29
0 o8 6
0 o35
0o90
0o98
0 o31
0 o3 3
1 o70
0 o74
0o00
1 o05
0 o4 8
Oo 2 2
0o67
1 o04
0o21
0o63
1 o22
1 o4 4
0o50
0 o59
0o77
0 o90
lo!3
Oo 30
lolO
1 o29
OoOO
0 o9 6
O.o91
0 o44
0o99
1 o59
lo20
0 =86
0o90
0o98
0o41
0 o94
1 o21
1 o16
0 =99
1 02 8
Oo 50
41
50
52
41
49
61
0
45
35
42
63
42
40
48
60
50
47
71
44
51
57
58
50
40
50
55
31
68
42
78
34
53
71
39
49
72
52
26
0
50
.59
53
0
WIDTH
45
18
39
53
48
29
0
37
24
43
32
18
22
0
0
40
40
0
44
28
37
49
66
19
29
45
42
50
22
58
51
0
54
30
37
0
28
32
0
66
42
41
39
THICK
7
4
7
7
7
8
0
7
6
8
4
4
3
9
8
13
12
15
8
5
7
18
14
4
12
11
8
11
7
15
7
14
7
9
13
8
5
5
20
8
11
11
5
IPA
EPA
0
0
0
0
0
0
0
0
0
0
96
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
64
76
0
0
79
0
60
84
0
0
76
0
56
69
0
0
69
63
0
0
79
87
72
0
74
0
0
84
61
83
69
59
0
78
72
0
81
46
77
75
79
60
66
Table II-2— Continued, Raw data listing of Tabun samples for metric
variables.
NAME
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
LY
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
Pw
PT
2 = 36
5o 91
4o 28
2,48
lo 89
lo 38
1 o 65
lo 09
3o 75
2o 01
2 o 81
2 o 70
0 o00
2. 15
2o 33
2o 44
7 o 39
3o 90
lo 84
3 o05
4» 13
4 o 57
4o 32
2 o86
3o 46
0o 79
lo 13
3o 11
lo 55
lo 34
2 o 73
lo 04
2o 75
2 o53
lo 70
lo 23
lo 26
2 o60
2 o 23
0 o 66
4o 60
2 o 07
lo 77
0 o00
1 o27
0o99
0o62
0 o9 5
0o74
0o45
0 o37
0o50
0o87
1 o61
1 o20
0 o0 0
0o70
0 068
1 o05
1 o77
2 o13
1 ol 4
1 o20
1 o09
1 o02
0 095
lolO
1 o2 3
0 =42
0 o52
1 o13
0o 24
0 o69
0o 58
0 o8 6
0o84
0o59
0o 75
0o43
0 o00
0 o70
Oo 52
0o37
lo27
0 o84
1 o20
LENGTH
68
71
25
31
45
67
51
53
34
28
48
59
58
63
72
37
107
99
78
79
55
52
41
22
0
40
57
46
45
40
43
0
47
60
0
0
49
44
39
50
0
68
0
WIDTH
45
55
47
45
27
28
42
34
36
31
35
33
46
30
29
20
99
68
35
53
63
49
51
29
37
35
25
33
36
37
36
0
33
33
0
40
37
32
29
41
0
32
0
THICK
10
13
10
4
10
8
7
11
6
6
13
11
7
10
7
5
21
15
15
22
6
6
7
7
10
5
7
11
4
8
5
14
6
6
11
11
14
9
5
13
10
6
17
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
111
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
69
58
72
0
r 80
89
0
65
0
0
66
0
31
74
56
61
62
75
70
70
0
60
42
52
86
76
64
87
79
79
75
74
72
75
82
0
0
66
0
60
69
0
Table II-2— ^Continued
NAME
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
Raw data listing of Tabun samples for metric
variableso
PW
PT
LENGTH
WIDTH
2o 23
2o 32
2 o 04
0o 60
2o 57
lo 82
lo 54
2o 43
3o 78
lo 66
l o 30
2o 55
4 o10
0 o98
1 o99
3 o18
0o 00
2 o 85
lo 60
lo 78
lo 81
2 o67
2 o17
3 o 44
2o 18
2o 25
lo 69
2 o90
lo 76
0o 77
2o 60
lo 89
1 o67
2o 00
2o 11
lo 69
lo 06
2 o 36
2 616
lo 01
lo 14
2o 25
lo 51
lo00
0o61
lo00
0 o29
0o59
1 o2 3
0 o61
0 o7 5
1 o48
0 o86
0 o57
0o 9 5
0 o79
0 o51
0 o70
0o 50
0o00
loll
0 o67
loll
0o 8 0
0 o63
0o 57
1 o35
1 o0 4
0o 61
0 o61
1 o58
0o52
0o 45
0o65
0o 75
0 o97
0o 5 5
loOO
0o49
0o 3 7
0o8 3
0 o64
0 o82
0o41
1 o2 3
0 o31
0
65
0
62
39
52
42
0
66
32
74
30
0
0
70
38
53
32
0
52
57
0
62
0
48
51
36
48
0
0
29
61
0
39
0
0
0
43
59
47
73
51
58
46
21
53
43
31
30
56
31
51
37
28
30
0
30
40
38
39
38
30
24
34
35
42
0
34
36
25
35
37
35
24
37
0
27
30
27
35
38
38
24
25
28
47
THICK
.
7
10
10
8
16
16
12
11
13
7
4
7
11
6
12
11
5
12
8
9
9
7
14
14
9
16
6
16
14
10
8
12
14
6
8
6
8
9
8
7
10
12
4
IPA
.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
O'
0
0
0
0
0
0
0
ERA
74
78
67
0
72
66
73
80
71
77
72
57
77
79
76
0
0
62
79
64
82
62
0
59
64
o
47
66
0
0
64
78
73
66
76
77
0
81
76
76
79
63
81
,
Table 11=2— Continued
Raw data listing of Tabun samples for metric
variableso
NAME
PW
PT
LENGTH
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
1 =15
Oo 50
1=74
1 =90
1= 11
2= 29
1= 23
1 =45
2 =61
3= 18
1= 08
3=04
1 =24
2= 28
0 =64
1=34
1= 09
2= 37
1 = 67
1 =06
2=93
1 =06
1 =67
1=12
3= 00
0=59
2= 81
2 =90
2= 60
2= 40
3= 32
0 =77
1 = 12
2= 98
4 =60
1=61
2=41
2 = 32
1 =05
1 =45
1=03
0=77
1=90
0 =36
0 =25
0 =46
0 =66
0 =48
0 =40
0 =38
0 =47
1 =25
0 =93
0 =32
1 =62
0 =48
1 =06
0 =26
0 =51
0 =40
0 =79
0=00
0=47
0 =80
0 =45
1=04
0 =55
0 =78
0 =21
0 =81
0 =89
0 =93
1 =27
0 =82
0 =29
0 =31
0 =80
1 =53
0 =51
0 =96
1=01
0 =37
0 =43
0 =44
0 =21
0 =34
46
0
39
57
31
54
51
45
0
37
55
68
46
81
62
33
50
0
75
42
60
45
54
42
50
43
59
0
49
0
55
48
52
41
93
67
0
45
44
50
47
54
0
WIDTH
14
36
35
29
30
47
21
0
47
37
0
45
20
36
35
24
36
0
32
23
41
35
45
16
27
30
38
30
0
0
33
31
15
30
41
27
40
44
16
19
28
44
26
THICK
7
7
5
13
5
8
7
3
14
7
8
18
8
10
15
8
11
16
9
10
7
8
13
6
8
7
11
8
15
18
11
6
6
6
16
16
17
12
5
5
4
5
6
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
116
0
0
0
0
0
104
0
0
0
112
114
0
0
0
0
0
0
110
0
0
113
0
0
0
0
0
108
0
63
0
87
0
70
0
74
0
73
70
0
0
77
77
98
80
0
0
0
86
71
92
83
77
74
86
85
70
74
81
0
0
76
56
62
71
0
72
0
0
59
56
0
Table 11=2— Continued
NAME
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
XIV
PW
1 o09
. 1 o77
4 o05
3 o56
2o 80
2o 26
2 a 78
2o 14
2b 70
lo 50
lo 78
1 = 88
3o 46
4o 03
4o 34
2b 30
Raw data listing of Tabun samples for metric
variableso
PT
LENGTH
0o27
0o 72
0b 82
1 b26
0 b93
0 b0 0
1 o40
0 =75
0 b9 3
0 o48
0 o59
0 b82
1 o05
1 o41
1 b24
0b80
39
43
42
0
0
0
0
78
0
72
0
-43
0
51
50
36
WIDTH
26
24
35
0
0
58
0
32
0
22
41
23
0
45
34
26
THICK
9
3
13
19
8
10
15
15
19
6
10
12
19
12
6
4
IPA
EPA
0
0
0
0
0
0
0
0
0
0
0
116
0
0
0
0
0
59
0
0
71
0
74
97
0
61
86
68
0
58
49
47
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