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Statistical Models
Theory and Practice

2nd Edition


  • Date Published: June 2009
  • availability: Available
  • format: Paperback
  • isbn: 9780521743853

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About the Authors
  • 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
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    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.' Persi Diaconis, Stanford University

    'This book is outstanding for the clarity of its thought and writing. It prepares readers for a critical assessment of the technical literature in the social and health sciences, and provides a welcome antidote to the standard formulaic approach to statistics.' Erich L. Lehmann, University of California, Berkeley

    'In Statistical Models, David Freedman explains the main statistical techniques used in causal modeling - and where the skeletons are buried. Complex statistical ideas are clearly presented and vividly illustrated with interesting examples. Both newcomers and practitioners will benefit from reading this book.' Alan Krueger, Princeton University

    'Regression techniques are often applied to observational data with the intent of drawing causal conclusions. In what circumstances is this justified? What are the assumptions underlying the analysis? Statistical Models answers these questions. The book is essential reading for anybody who uses regression to do more than summarize data. The treatment is original, and extremely well written. Critical discussions of research papers from the social sciences are most insightful. I highly recommend this book to anybody who engages in statistical modeling, or teaches regression, and most certainly to all of my students.' Aad van der Vaart, Vrije Universiteit Amsterdam

    'A pleasure to read, 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, Yale University

    'Statistical Models, a modern introduction to the subject, discusses graphical models and simultaneous equations among other topics. There are plenty of instructive exercises and computer labs. Especially valuable is the critical assessment of the main 'philosophers's stones' in applied statistics. This is an inspiring book and a very good read, for teachers as well as students.' Gesine Reinert, Oxford University

    '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.' Mathematical Reviews

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    Product details

    • Edition: 2nd Edition
    • Date Published: June 2009
    • format: Paperback
    • isbn: 9780521743853
    • length: 458 pages
    • dimensions: 244 x 168 x 25 mm
    • weight: 0.75kg
    • contains: 21 b/w illus. 11 tables 404 exercises
    • availability: 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.

  • Resources for

    Statistical Models

    David A. Freedman

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  • Instructors have used or reviewed this title for the following courses

    • Advanced Methods for Applied Microeconomics
    • Advanced Statistical Methods
    • Advanced Statistics
    • Advanced Topics in Political Analysis
    • An Overview of Quantitative Methods in Psychology
    • Analytical Techniques in Public Policy
    • Applied Correlation and Regression Methods in Education
    • Applied Linear Regression
    • Applied Statistical Methods
    • Applied Statistics
    • Applied Statistics I, Applied Statistics ll
    • Business and Economics Statistics
    • Data Analysis and Visualization
    • Economic Statistics and Econometrics
    • Empirical Research for Social Science & Policy
    • Introduction to Biostatistics ll
    • Introduction to Mathematical Statistics I, ll, llI
    • Introduction to Political Science (Concentration in Methods)
    • Introductory Graduate Statistics Sequence (ANOVA/Regression)
    • Latent Variable Models
    • Mathematical Probability and Mathematical Statistics
    • Methods of Political Research I
    • Policy Analysis & Program Evaluation
    • Political Science Methods; Data Analysis
    • Quantitative Methods ll
    • Quantitative Political Methodology
    • Quantitative Research Methods
    • Stat Methods for Business Research I
    • Statistical Modeling for Sustainability
    • Statistics analysis
    • Statistics for Management ll
    • Statistics for Public Policy
    • Statistics for the Social Sciences
  • Author

    David A. Freedman, University of California, Berkeley
    David A. Freedman is Professor of Statistics at the University of California, Berkeley. He has also taught in Athens, Caracas, Jerusalem, Kuwait, London, Mexico City, and Stanford. He has written several previous books, including a widely used elementary text. He is one of the leading researchers in probability and statistics, with 200 papers in the professional literature. He is a member of the American Academy of Arts and Sciences. In 2003, he received the John J. Carty Award for the Advancement of Science from the National Academy of Sciences, recognizing his 'profound contributions to the theory and practice of statistics'. Freedman has consulted for the Carnegie Commission, the City of San Francisco, and the Federal Reserve, as well as several departments of the US government. He has testified as an expert witness on statistics in law cases that involve employment discrimination, fair loan practices, duplicate signatures on petitions, railroad taxation, ecological inference, flight patterns of golf balls, price scanner errors, sampling techniques, and census adjustment.

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