Introduction to Social Statistics: The Logic of Statistical Reasoning by Thomas Dietz, Linda Kalof (original) (raw)

Table of contents 1. Linear models: some historical perspectives 8. Balanced linear models 2. Basic elements of linear algebra 9. The adequacy of Satterthwaite's approximation 3. Basic concepts in matrix algebra 10. Unbalanced fixed-effects models 4. The multivariate normal distribution 11. Unbalanced random and mixed models 5. Quadratic forms in normal variables 12. Additional topics in linear models 6. Full rank linear models 13. Generalized linear models 7. Less-than-full-rank linear models Readership: All readers interested in regression presented with a mix of theory and practice. The material on which this book is based has been taught in a couple of courses at the University of Florida for about 20 years and the author's skills and experience in doing this are superbly represented in this fine text. The presentation itself leans more toward the theoretical aspects, but there are numerous exercises that reinforce both the theoretical and the practical aspects of regression. (However, no solutions are provided.) "Chapters 11 and 12 can be particularly helpful to graduate students looking for dissertation topics." (Preface) This is an excellent, reliable, and comprehensive text.