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E-raamat: Exploratory Multivariate Analysis in Archaeology

  • Formaat: 330 pages
  • Sari: Foundations of Archaeology
  • Ilmumisaeg: 31-Dec-2015
  • Kirjastus: Eliot Werner Publications Inc
  • Keel: eng
  • ISBN-13: 9798986386195
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Exploratory Multivariate Analysis in ArchaeologySuurem pilt
  • Formaat: 330 pages
  • Sari: Foundations of Archaeology
  • Ilmumisaeg: 31-Dec-2015
  • Kirjastus: Eliot Werner Publications Inc
  • Keel: eng
  • ISBN-13: 9798986386195
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Explaining techniques of multivariate statistical analysis that are widely used in archaeology and archaeological science, Baxter emphasizes the popular methods of principal component analysis, correspondence analysis, cluster analysis, and discriminant analysis. The techniques described usually do not postulate an underlying model for the data, and often have the modest goal of reducing data to a form that may be used to inspect it for archaeologically useful structure or to present known structure in a compact form such as a two-dimensional plot. The book assumes readers to have, or be able and willing to acquire, a knowledge of elementary statistical methods. Annotation ©2015 Ringgold, Inc., Portland, OR (protoview.com)

Arvustused

'There are many things to admire about this book. . . . [ T]he treatment of the methods is very solid and to the point. I especially like the way in which Baxter explores their strengths and weaknesses in applied settings. . . . [ W]ritten at a level that most archaeologists will find comprehensible.' (Mark S. Aldenderfer, American Antiquity)





'[ A]n excellent tool and reference for the practicing archaeo-statistician, as well as for the novice who wishes to get acquainted with multivariate statistical methods. In it one obtains practical advice from an experienced practitioner . . . . I like this book and recommend it.' (Kenneth L Kvamme, Archaeological Computing Newsletter)





'[ A] no-nonsense account of the main multivariate techniques used in archaeology . . . . The style is straightforward and clear, and well in tune with the needs of the reader. . . . The tone is balanced and reasonable . . . . [ F]or anyone who analyses multivariate data in archaeology.' (Clive Orton, Journal of Archaeological Science)

List of Tables
xvii
List of Figures
xix
Acknowledgements xxi
1 Multivariate Statistics in Archaeology
1(26)
1.1 Introduction
1(1)
1.2 Multivariate analysis in archaeology
2(2)
1.3 Aspects of computer package use in archaeology
4(3)
1.4 What this book is not about
7(3)
1.5 Literature review
10(14)
1.5.1 Introduction
10(1)
1.5.2 Statistical texts
11(1)
1.5.3 Quantitative archaeology texts
11(1)
1.5.4 Journal and conference papers
11(1)
1.5.5 Analysis of chemical compositions of artefacts
12(3)
1.5.6 Typological/morphological studies
15(5)
1.5.7 Assemblage comparisons
20(3)
1.5.8 Inter- and intra-site spatial studies
23(1)
1.6 The structure of the book
24(3)
2 Univariate and Bivariate Approaches and Preliminary Data Analysis
27(21)
2.1 Introduction
27(1)
2.2 Data
27(1)
2.3 Dot-plots
28(2)
2.4 Box-plots
30(1)
2.5 Comparing groups
31(1)
2.6 Labelled scatterplots
32(1)
2.7 Looking at correlation matrices
33(5)
2.8 Assessing normality
38(2)
2.9 Transformations and linear combinations
40(2)
2.10 Tabular presentation
42(1)
2.11 Direct representation of multivariate data
43(2)
2.12 Notation, transformation and standardisation
45(3)
3 Principal Component Analysis -- The Main Ideas
48(15)
3.1 Introduction
48(1)
3.2 PCA as an exploratory method
48(4)
3.2.1 The aims of PCA
48(1)
3.2.2 A problem with PCA
49(1)
3.2.3 PCA as a linear combination of variables
49(1)
3.2.4 The geometry of PCA -- a simplified view
50(2)
3.3 Examples of PCA and some further considerations
52(11)
4 Principal Component Analysis -- Specialised Topics
63(37)
4.1 Introduction
63(1)
4.2 Distance and standardisation
63(2)
4.3 Covariance and correlation matrices
65(1)
4.4 Interpretation; biplots and related techniques
66(5)
4.5 Size and shape
71(1)
4.6 Compositional data and related problems
72(5)
4.7 Comparing configurations
77(2)
4.8 Outliers
79(1)
4.9 Mahalanobis distance
80(3)
4.10 Rotation of principal components
83(2)
4.11 Principal components and factor analysis
85(5)
4.12 An example
90(4)
4.13 Uses of PCA in archaeology
94(6)
5 Correspondence Analysis -- The Main Ideas
100(10)
5.1 Introduction
100(1)
5.2 Some examples of correspondence analysis in archaeology
101(6)
5.3 Correspondence analysis as principal component analysis
107(3)
6 Correspondence Analysis -- Extensions
110(30)
6.1 Introduction
110(1)
6.2 Correspondence analysis and chi-square distance
110(2)
6.3 A digression on the chi-squared test
112(1)
6.4 Correspondence analysis and chi-squared
113(1)
6.5 Decompositions of the inertia
114(4)
6.6 Correspondence analysis and seriation
118(5)
6.7 Multiple correspondence analysis
123(4)
6.8 Correspondence analysis of chemical compositions
127(1)
6.9 Examples
128(5)
6.10 Correspondence analysis in the archaeological literature
133(7)
7 Cluster Analysis -- The Main Ideas
140(14)
7.1 Introduction
140(1)
7.2 Some applications of cluster analysis in archaeology
141(13)
7.2.1 Chemical compositions and hierarchical agglomerative methods
141(6)
7.2.2 Relocation methods and k-means -- general ideas and an application
147(1)
7.2.3 Spatial analysis and k-means clustering
148(1)
7.2.4 Methods for binary data
149(3)
7.2.5 Mixed data and Gower's coefficient
152(2)
8 Cluster Analysis -- Some Problems
154(31)
8.1 Introduction
154(1)
8.2 Characteristics of clustering algorithms
154(7)
8.2.1 What types of cluster are to be expected?
154(2)
8.2.2 Choice of similarity measure
156(1)
8.2.3 Properties of clustering algorithms
157(2)
8.2.4 Conclusions regarding clustering algorithms
159(2)
8.3 Assessing cluster validity
161(4)
8.4 Comparing clusterings
165(2)
8.5 Problems with correlated variables
167(3)
8.6 Spatial clustering and related topics
170(2)
8.7 Mortuary studies and monothetic methods
172(1)
8.8 Other approaches
173(1)
8.9 An example
174(5)
8.10 Cluster analysis in archaeology
179(6)
9 Discriminant Analysis -- The Main Ideas
185(8)
9.1 Introduction
185(1)
9.2 Discriminant analysis
185(3)
9.3 The main ideas
188(5)
10 Further Aspects of Discriminant Analysis
193(26)
10.1 Introduction
193(1)
10.2 The mathematics of discriminant analysis
193(1)
10.3 Statistical inference
194(2)
10.4 The normality assumption
196(1)
10.5 The equal covariance matrices assumption
197(3)
10.6 Sample size
200(1)
10.7 Assessing how good discrimination is
201(3)
10.8 Use for validating clusters
204(2)
10.9 Variable selection
206(3)
10.10 Examples
209(5)
10.11 Discriminant analysis in the archaeological literature
214(5)
11 The Final
Chapter
219(8)
11.1 Introduction
219(1)
11.2 Developments in the statistical literature and archaeology
220(3)
11.2.1 Exploratory data analysis
220(1)
11.2.2 Miscellaneous multivariate methods
221(2)
11.3 Statistics in the archaeological literature
223(4)
11.3.1 Some generalities
223(1)
11.3.2 Statistics in archaeological publications
224(3)
Appendix A Data Sets 227(13)
Appendix B Matrix Algebra -- An Informal Guide 240(12)
Appendix C Computational Considerations 252(9)
Appendix D MV-ARCH and MV-NUTSHELLX 261(1)
Bibliography 262(42)
Index 304
M.J. Baxter is Professor Emeritus at Nottingham Trent University, UK.
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