Statistical Models
Statistical Models
This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.
- Authoritative guide by a well-known author with wide experience in teaching, research, and consulting
- Careful analysis of statistical issues in substantive applications
- New edition includes many new exercises and examples, and the author has reorganised, restructured and revised chapters to aid teaching and understanding
Reviews & endorsements
"At last, a second course in statistics that is serious, correct, and interesting. The book teaches regression, causal modeling, maximum likelihood, and the bootstrap. Everyone who analyzes real data should read this book, and we are extremely fortunate to now have the revised edition."
Persi Diaconis, Professor of Mathematics and Statistics, Stanford
University
"A pleasure to read, this newly revised edition of Statistical Models shows the field's most elegant writer at the height of his powers. While most textbooks hurry past core assumptions in order to explicate technique, this book places the spotlight on the core assumptions, challenging readers to think critically about how they are invoked in practice."
Donald Green, Professor of Political Science, Yale University
“For three decades, David Freedman has been the conscience of statistics as applied to important scientific, policy, and legal issues. This book is his legacy, and it is our great good fortune to have the new edition. It should be required reading for any user of multivariate models -- statistician or otherwise -- whose ultimate concern is not with statistical technique but rather with the substantive conclusions, if any, licensed by the data and the analysis.”
James M. Robins, Professor of Epidemiology and Biostatistics,
Harvard School of Public Health
"Statistical models: theory and practice is lucid, helpful, insightful and a joy to read. It focuses on the most common tools of applied statistics with a clear and simple presentation. This revised edition organizes the chapters differently, making reading much easier. Moreover, it includes many new examples and exercises. In summary, it is a nice and extremely useful addition to the statistical literature."
Heleno Balfarine, Mathematical Reviews
Product details
April 2009Paperback
9780521743853
458 pages
244 × 168 × 25 mm
0.75kg
21 b/w illus. 11 tables 404 exercises
Available
Table of Contents
- 1. Observational studies and experiments
- 2. The regression line
- 3. Matrix algebra
- 4. Multiple regression
- 5. Multiple regression: special topics
- 6. Path models
- 7. Maximum likelihood
- 8. The bootstrap
- 9. Simultaneous equations
- 10. Issues in statistical modeling.
