Statistics in Archaeology

Statistics in Archaeology

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 300 p.
  • 言語 ENG
  • 商品コード 9780340762998
  • DDC分類 930.1015195

Table of Contents

Preface                                            ix
1 Introduction 1 (18)
1.1 Statistics and archaeology 1 (2)
1.1.1 Introduction 1 (1)
1.1.2 Statistical use in archaeology 2 (1)
1.2 Statistics in archaeology 3 (13)
1.2.1 The background 3 (5)
1.2.2 Landmark and other papers 8 (5)
1.2.3 Other literature 13 (3)
1.3 Simple statistics? 16 (3)
2 Data sets and problems 19 (10)
2.1 Introduction 19 (1)
2.2 Data 19 (10)
2.2.1 Lead isotope ratio data 19 (1)
2.2.2 Artifact compositional data 20 (2)
2.2.3 Artifact typology 22 (1)
2.2.4 Assemblage comparison I 23 (1)
2.2.5 Assemblage comparison II 24 (3)
2.2.6 Spatial data 27 (2)
3 Kernel density estimates 29 (9)
3.1 Introduction 29 (1)
3.2 Kernel density estimates 30 (3)
3.2.1 Univariate KDES 30 (2)
3.2.2 Multivariate KDES 32 (1)
3.3 Applications 33 (5)
3.3.1 Italian Bronze Age cups 33 (2)
3.3.2 The Mask Site bone splinter data 35 (1)
3.3.3 Other applications 36 (2)
4 Sampling 38 (12)
4.1 Introduction 38 (1)
4.2 Sampling methods 39 (4)
4.2.1 Notation 39 (1)
4.2.2 Simple random sampling 40 (1)
4.2.3 Stratified random sampling 41 (1)
4.2.4 Cluster sampling 41 (2)
4.2.5 Systematic sampling 43 (1)
4.3 Archaeological considerations 43 (3)
4.3.1 Random versus purposive sampling 43 (2)
4.3.2 What is being sampled? 45 (1)
4.4 Adaptive sampling 46 (1)
4.5 Sampling for discovery/rare features 47 (3)
4.5.1 Sampling for discovery 47 (2)
4.5.2 Sampling for 'nothing' 49 (1)
5 Regression and related models 50 (16)
5.1 Introduction 50 (2)
5.2 Simple linear regression 52 (3)
5.2.1 An example 52 (2)
5.2.2 Models for data 54 (1)
5.2.3 Flake size and flake-size distribution 54 (1)
5.3 Multiple linear regression 55 (4)
5.3.1 The basic model 55 (1)
5.3.2 Polynomial regression and related 56 (1)
models
5.3.3 Trend-surface analysis 56 (1)
5.3.4 Regression with 0-1 dependent 57 (1)
variables
5.3.5 Regression with 0-1 independent 58 (1)
variables
5.4 Generalized linear models 59 (3)
5.4.1 Basic ideas 59 (1)
5.4.2 Logistic regression 60 (2)
5.5 Non-linear regression 62 (1)
5.6 Non-parametric regression 63 (3)
6 Multivariate methods - an introduction 66 (7)
6.1 Introduction 66 (1)
6.2 Notation and terminology 66 (2)
6.3 The singular value decomposition 68 (1)
6.4 Measures of distance 68 (5)
6.4.1 Manhattan distance 68 (1)
6.4.2 Euclidean distance 69 (1)
6.4.3 Mahalanobis distance 69 (4)
7 Principal component analysis and related 73 (17)
methods
7.1 Introduction 73 (1)
7.2 Aspects of principal component analysis 74 (9)
7.2.1 The mathematics 74 (1)
7.2.2 Transformation 74 (4)
7.2.3 Biplots 78 (1)
7.2.4 Choosing the number of components 79 (1)
7.2.5 Rotation 80 (3)
7.3 Factor analysis 83 (2)
7.4 Multidimensional scaling 85 (3)
7.4.1 The main ideas 85 (1)
7.4.2 Example: Analysis of ceramic 86 (2)
thin-section data
7.5 Projection pursuit 88 (2)
8 Cluster analysis 90 (15)
8.1 Introduction 90 (2)
8.2 Hierarchical clustering methods 92 (5)
8.2.1 Hierarchical agglomerative clustering 92 (3)
8.2.2 Hierarchical divisive clustering 95 (1)
8.2.3 Hierarchical clustering methods in 96 (1)
burial studies
8.3 Relocation/partitioning methods 97 (2)
8.3.1 Main ideas 97 (1)
8.3.2 A case study 98 (1)
8.4 Model-based methods 99 (6)
8.4.1 Classification maximum likelihood 99 (1)
8.4.2 Mixture maximum likelihood 100(1)
8.4.3 Archaeological applications 101(4)
9 Discrimination and classification 105(14)
9.1 Introduction 105(1)
9.2 Linear and quadratic discriminant analysis 106(8)
9.2.1 Normal-theory LDA and QDA 106(1)
9.2.2 Fisher's LDA 107(1)
9.2.3 Assessing the success of a 108(2)
classification
9.2.4 Two-group discriminant analysis and 110(1)
regression
9.2.5 Variable selection 111(1)
9.2.6 Quadratic discriminant analysis 111(1)
9.2.7 Examples. 112(2)
9.3 Logistic discrimination 114(2)
9.4 Classification trees 116(3)
10 Missing data and outliers 119(9)
10.1 Missing and censored data 119(4)
10.1.1 Introduction 119(1)
10.1.2 Missing data 119(2)
10.1.3 Censored data 121(1)
10.1.4 An EM algorithm 122(1)
10.2 Outliers 123(5)
11 Analysis of tabular data 128(19)
11.1 Introduction 128(1)
11.2 Chi-squared analysis of contingency 129(2)
tables
11.2.1 Two-way tables 129(1)
11.2.2 Three-way tables 129(2)
11.3 Log-linear models 131(5)
11.3.1 Three-way tables 131(4)
11.3.2 Four-way tables - an example 135(1)
11.4 Correspondence analysis 136(7)
11.4.1 Introduction 136(3)
11.4.2 Detrended correspondence analysis 139(1)
11.4.3 Multiple correspondence analysis - 140(1)
example
11.4.4 Some applications 140(3)
11.5 The mathematics of correspondence 143(4)
analysis
11.5.1 Chi-square distance 143(1)
11.5.2 Correspondence analysis as PCA 144(1)
11.5.3 Matrix formulations 144(1)
11.5.4 Multiple correspondence analysis - 145(2)
theory
12 Computer-intensive methods 147(12)
12.1 Introduction 147(1)
12.2 The bootstrap 148(5)
12.2.1 Basic ideas 148(1)
12.2.2 Examples of bootstrapping 148(5)
12.3 The jackknife 153(1)
12.4 Other applications of randomization 154(3)
12.4.1 Buildings at Danebury 154(1)
12.4.2 Bronze Age cairns on Mull 155(1)
12.4.3 Artifacts in graves 155(2)
12.5 Markov chain Monte Carlo 157(2)
13 Spatial analysis 159(17)
13.1 Introduction 159(1)
13.2 Spatial clustering 160(2)
13.3 Predictive modeling 162(1)
13.4 Point pattern analysis 163(6)
13.4.1 Nearest neighbor analysis 163(2)
13.4.2 Applications of nearest neighbor 165(1)
analysis
13.4.3 Second-order methods 166(2)
13.4.4 Applications of second-order methods 168(1)
13.5 Spatial autocorrelation 169(4)
13.5.1 Introduction 169(1)
13.5.2 The Classic Maya collapse 169(3)
13.5.3 Spatial patterns among blood types 172(1)
13.6 Shape analysis 173(3)
13.6.1 Introduction 173(1)
13.6.2 Post-hole patterns 173(2)
13.6.3 Comparing shapes 175(1)
14 Bayesian methods 176(11)
14.1 Bayes' theorem 176(2)
14.2 Bayesian inference in archaeology - an 178(1)
overview
14.3 Bayesian inference in archaeology - 179(7)
examples
14.3.1 Estimating proportions 179(3)
14.3.2 Bayesian clustering 182(3)
14.3.3 A miscellany 185(1)
14.4 Discussion 186(1)
15 Absolute dating - radiocarbon calibration 187(13)
15.1 Introduction 187(2)
15.2 Combining dates 189(2)
15.2.1 Theory 189(1)
15.2.2 Application 190(1)
15.3 Some Bayesian solutions 191(7)
15.3.1 Calibration of a single date 191(1)
15.3.2 Multiple dates - single phase 192(1)
15.3.3 Multiple dates - ordered 193(1)
15.3.4 Multiple dates - multiple phases 194(2)
15.3.5 Prior assumptions 196(2)
15.4 Other applications 198(2)
15.4.1 Outlier detection 198(1)
15.4.2 Sample selection 198(2)
16 Relative dating - seriation 200(10)
16.1 Introduction 200(2)
16.2 A brief review 202(1)
16.3 Practical seriation 203(4)
16.3.1 Similarity matrices 203(1)
16.3.2 Correspondence analysis and MDS 204(3)
16.3.3 Bayesian methods 207(1)
16.4 Archaeological considerations 207(3)
17 Quantification 210(12)
17.1 Introduction 210(1)
17.2 Quantification of vertebrate faunal 211(4)
remains
17.2.1 Simple approaches to quantification 211(1)
17.2.2 Models - the Lincoln/Peterson index 212(1)
17.2.3 Maximum likelihood estimation of 213(2)
bone counts
17.3 Pottery quantification 215(4)
17.3.1 Introduction 215(1)
17.3.2 Simple measures and estimated vessel 216(1)
equivalents
17.3.3 Pottery information equivalents 217(2)
17.4 Other find types and the pie-slice 219(3)
approach
17.4.1 Bone 219(1)
17.4.2 Glass 220(1)
17.4.3 Stone tools 221(1)
18 Lead isotope analysis 222(6)
18.1 Introduction 222(1)
18.2 Statistical issues 223(4)
18.2.1 Data transformation 223(1)
18.2.2 Outliers 224(1)
18.2.3 Normality 224(2)
18.2.4 Sample size 226(1)
18.3 Conclusion 227(1)
19 The megalithic yard 228(8)
19.1 Introduction 228(2)
19.2 Models for the megalithic yard 230(4)
19.2.1 The basic model 230(1)
19.2.2 Broadbent's method 230(1)
19.2.3 Kendall's method 231(2)
19.2.4 Freeman's method 233(1)
19.3 Discussion 234(2)
20 Comparing assemblage diversity 236(8)
20.1 Introduction 236(1)
20.2 Diversity 236(2)
20.3 Regression and the sample-size effect 238(2)
20.4 Simulation and the sample-size effect 240(3)
20.5 Resampling approaches 243(1)
21 Shorter studies 244(4)
21.1 Introduction 244(1)
21.2 Artifact classification 244(1)
21.3 Age estimation 245(1)
21.4 Particle-size analysis 246(2)
Appendix-Web resources 248(3)
A.1 S-Plus and R 248(1)
A.2 Other resources 249(2)
References 251(37)
Index 288