Doing Bayesian Data Analysis: A Tutorial with R, Stan, brms, and the tidyverse Kindle Edition

Doing Bayesian Data Analysis: A Tutorial with R, Stan, brms, and the tidyverse , Third Edition, provides a carefully scaffolded tutorial from beginning concepts to advanced, realistic data analyses. The book uses a proven sequence of topics unique to Doing Bayesian Data Analysis. The first part covers foundational concepts of statistical models, probability, Bayesian reasoning, and computer programming in R and the tidyverse. The second part introduces all the concepts and methods of Bayesian data analysis, including the Stan modeling language, by using the simplest possible data structures and statistical models. The third part covers the generalized linear model, including multilevel (a.k.a. hierarchical) versions of regression and analysis of variance, for a variety of data types (metric, ordinal, nominal, dichotomous, count), using the convenient computer package called brms. Every concept and case is illustrated with detailed examples, and all computer code is available at the book's website. This book is intended for self-learners or classroom learning, for first-year graduate students, advanced undergraduates, and professionals. The methods apply to any field, including social sciences, biological sciences, and physical sciences, for any setting, including academia, government, business, and industry.•Accessible to beginners, introducing basic concepts of probability and computer programming. •Carefully scaffolds to advanced models for realistic data analysis, using a proven progression of topics unique to Doing Bayesian Data Analysis. •Numerous complete examples with the computer software R, Stan, brms, and the tidyverse. •Comprehensive coverage of the generalized linear model, including multilevel (a.k.a. hierarchical) versions of regression and traditional analysis of variance. •Coverage of experiment sample-size planning (analogous to traditional power analysis) and model-comparison techniques. • Examples abide by the Bayesian Analysis Reporting Guidelines. Read more