This section will review those books whose content and level reflect the general editorial policy of Technometrics. Publishers should send books for review to Ejaz Ahmed, Department of Mathematics and Sciences, Brock University, St. Catharines, ON L2S 3A1 (mailto:[email protected]).
The opinions expressed in this section are those of the reviewers. These opinions do not represent positions of the reviewer’s organization and may not reflect those of the editors or the sponsoring societies. Listed prices reflect information provided by the publisher and may not be current.
The book purchase programs of the American Society for Quality can provide some of these books at reduced prices for members. For information, contact the American Society for Quality at 1-800-248-1946.
Lectures on Categorical Data Analysis
Tamás Rudas Subir Ghosh 560
Bayesian Inference—Data Evaluation and Decisions (2nd ed.)
Hanns Ludwig Harney Jian Guo 561
Digital Humanities and Film Studies: Visualising Dziga Vertov’s Work
Adelheid Heftberger Stan Lipovetsky 562
Simulating Societal Change: Counterfactual Modelling for Social and Policy Inquiry
Peter Davis and Roy Lay-Yee Stan Lipovetsky 563
Exploratory Data Analysis With MATLAB (3rd ed.)
Wendy L. Martinez, Angel R. Martinez, and Jeffery L. Solka Morteza Marzjarani 565
Foundations of Info-Metrics (Modeling, Inference and Imperfect Information)
Amos Golan Nozer D. Singpurwalla and Lai Boya 566
Editor Reviews
Risk and Reward: The Science of Casino Blackjack (2nd ed.)
Richard Werthamer S. Ejaz Ahmed 567
Continuous Time Modeling in the Behavioural and Related Sciences
Kees van Montfort, Johan H. L. Oud, and Manuel C. Voelkle S. Ejaz Ahmed 567
Dynamic Neuroscience Statistic, Modeling, and Control
Zhe Chen and Sridevi V. Sarma (Eds.) S. Ejaz Ahmed 568
Partial Least Squares Path Modeling
Hengky Latan and Richard Noonan (eds.) S. Ejaz Ahmed 568
Lectures on Categorical Data Analysis is an outstanding book presenting the fundamental results in categorical data analysis. This book is presented at the level of an upper division undergraduate class or a first year graduate class. It can be used for both reference and self-study. The book combines “mathematical precision and intuition” and links “theory with the everyday practice of data collection and analysis.”
There are 13 chapters: 1. The Role of Categorical Analysis, 2. Sampling Distributions, 3. Normal Approximations, 4. Simple Estimation for Categorical Data, 5. Basic Testing for Categorical Data, 6. Association, 7. Latent Classes and Exponential Families, 8. Effects and Associations, 9. Simpson’s Paradox, 10. Log-Linear Models: Definition, 11. Log-Linear Models: Interpretation, 12. Log-Linear Models: Estimation, and 13. What’s Next.
The last section of each chapter: Things to Do, contains 20 or more problems for the most of them and between 15 and 20 for the remaining of them. There are more than 200 problems in the book. Most of these problems are more challenging than the simple exercises.
The book has created its own place in the area of categorical data analysis. I enjoyed reading this book and learned a lot from it. I strongly recommend it to anyone who would like to learn more about the area of categorical data analysis.
University of California, Riverside