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To foster a deeper understanding of the interconnection of the social sciences, economists should know where historical data come from, sociologists should know how to think like economists, political scientists would benefit from understanding how models are tested in psychology, historians should learn how political processes are studied, psychologists should understand sociological theories, and so forth. This overview by prominent social scientists gives an accessible, non-technical sense of how quantitative research is done in the social sciences. Upon finishing this book, the reader...

On the night of the 2000 presidential election, Americans watched on television as polling results divided the nation's map into red and blue states. Since then the color divide has become symbolic of a culture war that thrives on stereotypes--pickup-driving red-state Republicans who vote based on God, guns, and gays; and elitist blue-state Democrats woefully out of touch with heartland values. With wit and prodigious number crunching, Andrew Gelman debunks these and other political myths.

This expanded edition includes new data and easy-to-read graphics explaining the 2008...

To foster a deeper understanding of the interconnection of the social sciences, economists should know where historical data come from, sociologists should know how to think like economists, political scientists would benefit from understanding how models are tested in psychology, historians should learn how political processes are studied, psychologists should understand sociological theories, and so forth. This overview by prominent social scientists gives an accessible, non-technical sense of how quantitative research is done in the social sciences. Upon finishing this book, the reader...

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference,...

This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data.

Key features of the book include:

• Comprehensive coverage of an imporant area for both research and applications.
• Adopts a pragmatic...

Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active student participation.

Part I of the book presents a large selection of activities for introductory statistics courses and has...

Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active student participation.

Part I of the book presents a large selection of activities for introductory statistics courses and has...

Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors all leaders in the statistics community introduce basic concepts from a data-analytic perspective before presenting advanced methods....