Best Andrew Gelman books
Data Analysis Using Regression and Multilevel/Hierarchical Models
Andrew Gelman
Best price for this book: $ 38.97
Teaching Statistics: A Bag of Tricks
Andrew Gelman
Best price for this book: $ 25.86
Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class' with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn't, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.
Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
Andrew Gelman
Best price for this book: $ 57.69
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 uptodate Bayesian methods. The authors―all leaders in the statistics community―introduce basic concepts from a dataanalytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice.
New to the Third Edition
 Four new chapters on nonparametric modeling
 Coverage of weakly informative priors and boundaryavoiding priors
 Updated discussion of crossvalidation and predictive information criteria
 Improved convergence monitoring and effective sample size calculations for iterative simulation
 Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation
 New and revised software code
The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do
Andrew Gelman
Best price for this book: $ 10.39
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 stereotypespickupdriving redstate Republicans who vote based on God, guns, and gays; and elitist bluestate 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 easytoread graphics explaining the 2008 election. Red State, Blue State, Rich State, Poor State is a mustread for anyone seeking to make sense of today's fractured political landscape.
Statistics Done Wrong: The Woefully Complete Guide
Alex Reinhart
Best price for this book: $ 15
Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunderfree. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics.
You'll find advice on:
 Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan
 How to think about p values, significance, insignificance, confidence intervals, and regression
 Choosing the right sample size and avoiding false positives
 Reporting your analysis and publishing your data and source code
 Procedures to follow, precautions to take, and analytical software that can help
The first step toward statistics done right is Statistics Done Wrong.
Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman & Hall/CRC Texts in Statistical Science)
Richard McElreath
Best price for this book: $ 76.21
Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s modelbased statistics, the book pushes readers to perform stepbystep calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.
The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.
By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.
Web Resource
The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan
John Kruschke
Best price for this book: $ 67.11
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are stepbystep instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact highlevel scripts that make it easy to run the programs on your own data sets.
The book is divided into three parts and begins with the basics: models, probability, Bayes’ rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metricpredicted variable on one or two groups; metricpredicted variable with one metric predictor; metricpredicted variable with multiple metric predictors; metricpredicted variable with one nominal predictor; and metricpredicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment.
This book is intended for firstyear graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business.
 Accessible, including the basics of essential concepts of probability and random sampling
 Examples with R programming language and JAGS software
 Comprehensive coverage of all scenarios addressed by nonBayesian textbooks: ttests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chisquare (contingency table analysis)
 Coverage of experiment planning
 R and JAGS computer programming code on website
 Exercises have explicit purposes and guidelines for accomplishment

Provides stepbystep instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs
Teaching Statistics: A Bag of Tricks
Andrew Gelman
Best price for this book: $ 59.99
A Quantitative Tour of the Social Sciences
Best price for this book: $ 39.99
By Andrew Gelman Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (Expanded Edition) (Expanded)
Best price for this book: $ 26.04