'This book is an introduction to the principles and methodology of modern multivariate statistical analysis. It is written for the user and potential user of multivariate techniques as well as for postgraduate students coming to the subject for the first time. The author\'s emphasis is problem-oriented; he stresses geometrical intuition in preference to algebraic manipulation. Mathematical sections which are not essential for a practical understanding of technique are clearly indicated so they may be skipped by nonspecialists. The book covers recent developments concerning discrete and mixed variable techniques, as well as continuous variable techniques and other new ideas. This is an up-to-date and very readable account--with a practical emphasis--for research workers in subjects as diverse as anthropology, education, industry, medicine, and taxonomy.'

PART I: Looking at Multivariate Data

1. Motivation and Fundamental Concepts

2. One-Way Graphical Representation

3. Graphical Methods for Association or Proximity Matrices

4. Two-Way Graphical Representation of Data Matrices

5. Analytical Comparison of Two or More Graphical Representations

PART II: Samples, Populations, and Models

6. Data Inspection or Data Analysis?

7. Distribution Theory

PART III: Analysing Ungrouped Data

8. Estimation and Hypothesis Testing

9. Reduction of Dimensionality

10. Discrete Data

PART IV: Analysing Grouped Data

11. Incorporating Group Structure

12. Inferential Aspects: The Two-Group Case

13. Inferential Aspects: More Than Two Groups

PART V: Analysing Association Among Variables

14. Measuring and Interpreting Association

15. Exploiting Observed Associations: Manifest-Variable Models

16. Explaining Observed Associations: Latent-Variable Models

17. Conclusion: Some General Multivariate Problems