Foreword xv Preface xvii Part One Introduction 1 1 Data Visualisation 3 1.1 A Very Brief Introduction to Data Visualisation 3 1.1.1 A Very Brief History 3 1.1.2 Introduction to Visualisation Tools for Numerical Data4 1.1.3 Introduction to Visualisation Tools for UnivariateCategorical Data 6 1.

2 Data Visualisation for Contingency Tables 10 1.2.1 Fourfold Displays 11 1.3 Other Plots 12 1.4 Studying Exposure to Asbestos 13 1.4.1 Asbestos and Irving J. Selikoff 13 1.

4.2 Selikoff''s Data 17 1.4.3 Numerical Analysis of Selikoff''s Data 17 1.4.4 A Graphical Analysis of Selikoff''s Data 18 1.4.5 Classical Correspondence Analysis of Selikoff''s Data20 1.

4.6 Other Methods of Graphical Analysis 22 1.5 Happiness Data 25 1.6 Correspondence Analysis Now 29 1.6.1 A Bibliographic Taste 29 1.6.2 The Increasing Popularity of Correspondence Analysis29 1.

6.3 The Growth of the Correspondence Analysis Family Tree32 1.7 Overview of the Book 34 1.8 R Code 35 References 36 2 Pearson''s Chi-Squared Statistic 44 2.1 Introduction 44 2.2 Pearson''s Chi-Squared Statistic 44 2.2.1 Notation 44 2.

2.2 Measuring the Departure from Independence 45 2.2.3 Pearson''s Chi-Squared Statistic 47 2.2.4 Other 2 Measures of Association 48 2.2.5 The Power Divergence Statistic 49 2.

2.6 Dealing with the Sample Size 50 2.3 The Goodman--Kruskal Tau Index 51 2.3.1 Other Measures and Issues 52 2.4 The 2 × 2 Contingency Table 52 2.4.1 Yates'' Continuity Correction 53 2.

5 Early Contingency Tables 54 2.5.1 The Impact of Adolph Quetelet 55 2.5.2 Gavarret''s (1840) Legitimate Children Data 58 2.5.3 Finley''s (1884) Tornado Data 58 2.5.

4 Galton''s (1892) Fingerprint Data 59 2.5.5 Final Comments 61 2.6 R Code 61 2.6.1 Expectation and Variance of the Pearson Chi-SquaredStatistic 61 2.6.2 Pearson''s Chi-Squared Test of Independence 62 2.

6.3 The Cressie--Read Statistic 64 References 67 Part Two Correspondence Analysis of Two-Way Contingency Tables71 3 Methods of Decomposition 73 3.1 Introduction 73 3.2 Reducing Multidimensional Space 73 3.3 Profiles and Cloud of Points 74 3.4 Property of Distributional Equivalence 79 3.5 The Triplet and Classical Reciprocal Averaging 79 3.5.

1 One-Dimensional Reciprocal Averaging 80 3.5.2 Matrix Form of One-Dimensional Reciprocal Averaging 81 3.5.3 -Dimensional Reciprocal Averaging 83 3.5.4 Some Historical Comments 83 3.6 Solving the Triplet Using Eigen-Decomposition 84 3.

6.1 The Decomposition 84 3.6.2 Example 85 3.7 Solving the Triplet Using Singular Value Decomposition86 3.7.1 The Standard Decomposition 86 3.7.

2 The Generalised Decomposition 88 3.8 The Generalised Triplet and Reciprocal Averaging 89 3.9 Solving the Generalised Triplet Using Gram--Schmidt Process91 3.9.1 Ordered Categorical Variables and a priori Scores 91 3.9.2 On Finding Orthogonalised Vectors 92 3.9.

3 A Recurrence Formulae Approach 94 3.9.4 Changing the Basis Vector 96 3.9.5 Generalised Correlations 97 3.10 Bivariate Moment Decomposition 100 3.11 Hybrid Decomposition 100 3.11.

1 An Alternative Singly Ordered Approach 102 3.12 R Code 103 3.12.1 Eigen-Decomposition in R 103 3.12.2 Singular Value Decomposition in R 103 3.12.3 Singular Value Decomposition for Matrix Approximation104 3.

12.4 Generating Emerson''s Polynomials 106 3.13 A Preliminary Graphical Summary 109 3.14 Analysis of Analgesic Drugs 112 References 115 4 Simple Correspondence Analysis 120 4.1 Introduction 120 4.2 Notation 121 4.3 Measuring Departures from Complete Independence 122 4.3.

1 The ''Duplication Constant'' 123 4.3.2 Pearson Ratios 123 4.4 Decomposing the Pearson Ratio 124 4.5 Coordinate Systems 126 4.5.1 Standard Coordinates 126 4.5.

2 Principal Coordinates 127 4.5.3 Biplot Coordinates 132 4.6 Distances 136 4.6.1 Distance from the Origin 136 4.6.2 Intra-Variable Distances and the Metric 137 4.

6.3 Inter-Variable Distances 138 4.7 Transition Formulae 140 4.8 Moments of the Principal Coordinates 141 4.8.1 The Mean of 142 4.8.2 The Variance of 142 4.

8.3 The Skewness of 143 4.8.4 The Kurtosis of 143 4.8.5 Moments of the Asbestos Data 144 4.9 How Many Dimensions to Use? 145 4.10 R Code 147 4.

11 Other Theoretical Issues 154 4.12 Some Applications of Correspondence Analysis 156 4.13 Analysis of a Mother''s Attachment to Her Child158 References 165 5 Non-Symmetrical Correspondence Analysis 177 5.1 Introduction 177 5.2 The Goodman--Kruskal Tau Index 180 5.2.1 The Tau Index as a Measure of the Increase inPredictability 180 5.2.

2 The Tau Index in the Context of ANOVA 182 5.2.3 The Sensitivity of 182 5.2.4 A Demonstration: Revisiting Selikoff''s Asbestos Data185 5.3 Non-Symmetrical Correspondence Analysis 186 5.3.1 The Centred Column Profile Matrix 186 5.

3.2 Decomposition of 187 5.4 The Coordinate Systems 188 5.4.1 Standard Coordinates 188 5.4.2 Principal Coordinates 189 5.4.

3 Biplot Coordinates 193 5.5 Transition Formulae 197 5.5.1 Supplementary Points 198 5.5.2 Reconstruction Formulae 198 5.6 Moments of the Principal Coordinates 199 5.6.

1 The Mean of 199 5.6.2 The Variance of 200 5.6.3 The Skewness of 201 5.6.4 The Kurtosis of 201 5.7 The Distances 201 5.

7.1 Column Distances 201 5.7.2 Row Distances 203 5.8 Comparison with Simple Correspondence Analysis 204 5.9 R Code 204 5.10 Analysis of a Mother''s Attachment to Her Child209 References 212 6 Ordered Correspondence Analysis 216 6.1 Introduction 216 6.

2 Pearson''s Ratio and Bivariate Moment Decomposition221 6.3 Coordinate Systems 222 6.3.1 Standard Coordinates 222 6.3.2 The Generalised Correlations 223 6.3.3 Principal Coordinates 225 6.

3.4 Location, Dispersion and Higher Order Components 229 6.3.5 The Correspondence Plot and Generalised Correlations230 6.3.6 Impact on the Choice of Scores 232 6.4 Artificial Data Revisited 233 6.4.

1 On the Structure of the Association 233 6.4.2 A Graphical Summary of the Association 233 6.4.3 An Interpretation of the Axes and Components 234 6.4.4 The Impact of the Choice of Scores 235 6.5 Transition Formulae 236 6.

6 Distance Measures 238 6.6.1 Distance from the Origin 238 6.6.2 Intra-Variable Distances 239 6.7 Singly Ordered Analysis 239 6.8 R Code 241 6.8.

1 Generalised Correlations and Principal Inertias 241 6.8.2 Doubly Ordered Correspondence Analysis 245 References 248 7 Ordered Non-Symmetrical Correspondence Analysis 251 7.1 Introduction 251 7.2 General Considerations 252 7.2.1 Orthogonal Polynomials Instead of Singular Vectors 253 7.3 Doubly Ordered Non-Symmetrical Correspondence Analysis254 7.

3.1 Bivariate Moment Decomposition 254 7.3.2 Generalised Correlations in Bivariate Moment Decomposition255 7.4 Singly Ordered Non-Symmetrical Correspondence Analysis257 7.4.1 Hybrid Decomposition for an Ordered Predictor Variable257 7.4.

2 Hybrid Decomposition in the Case of Ordered ResponseVariables 258 7.4.3 Generalised Correlations in Hybrid Decomposition 258 7.5 Coordinate Systems for Ordered Non-SymmetricalCorrespondence Analysis 259 7.5.1 Polynomial Plots for Doubly Ordered Non-SymmetricalCorrespondence Analysis 260 7.5.2 Polynomial Biplot for Doubly Ordered Non-SymmetricalCorrespondence Analysis 262 7.

5.3 Polynomial Plot for Singly Ordered Non-SymmetricalCorrespondence Analysis with an Ordered Predictor Variable 262 7.5.4 Polynomial Biplot for Singly Ordered Non-SymmetricalCorrespondence Analysis with an Ordered Predictor Variable 263 7.5.5 Polynomial Plot for Singly Ordered Non-SymmetricalCorrespondence Analysis with an Ordered Response Variable 264 7.5.6 Polynomial Biplot for Singly Ordered Non-SymmetricalCorrespondence Analysis with an Ordered Response Variable 265 7.

6 Tests of Asymmetric Association 265 7.7 Distances in Ordered Non-Symmetrical Correspondence Analysis266 7.7.1 Distances in Doubly Ordered Non-Symmetrical CorrespondenceAnalysis 267 7.7.2 Distances in Singly Ordered Non-Symmetrical CorrespondenceAnalysis 269 7.8 Doubly Ordered Non-Symmetrical Correspondence of AsbestosData 269 7.8.

1 Trends 270 7.9 Singly Ordered Non-Symmetrical Correspondence Analysis ofDrug Data 277 7.9.1 Predictability of Ordered Rows Given Columns 278 7.10 R Code for Ordered Non-Symmetrical Correspondence Analysis283 References 300 8 External Stability and Confidence Regions 302 8.1 Introduction 302 8.2 On the Statistical Significance of a Point 303 8.3 Circular Confidence Regions for Classical CorrespondenceAnalysis 304 8.

4 Elliptical Confidence Regions for Classical CorrespondenceAnalysis 306 8.4.1 The Information in the Optimal Correspondence Plot 306 8.4.2 The Information in the First Two Dimensions 308 8.4.3 Eccentricity of Elliptical Regions 309 8.4.

4 Comparison of Confidence Regions 309 8.5 Confidence Regions for Non-Symmetrical Corresponde.