Introduction to Bayesian Data Analysis by Bruno Nicenboim (.ePUB)+
File Size: 52.9 MB
Introduction to Bayesian Data Analysis for Cognitive Science by Bruno Nicenboim, Daniel J. Schad, Shravan Vasishth
Requirements: .ePUB, .PDF reader, 52.9 MB
Overview: This book introduces Bayesian data analysis and Bayesian cognitive modeling to students and researchers in cognitive science (e.g., linguistics, psycholinguistics, psychology, computer science), with a particular focus on modeling data from planned experiments. The book relies on the probabilistic programming language Stan and the R package brms, which is a front-end to Stan. The book only assumes that the reader is familiar with the statistical programming language R, and has basic high school exposure to pre-calculus mathematics; some of the important mathematical constructs needed for the book are introduced in the first chapter. Through this book, the reader will be able to develop a practical ability to apply Bayesian modeling within their own field. The book begins with an informal introduction to foundational topics such as probability theory, and univariate and bi-/multivariate discrete and continuous random variables.
Genre: Non-Fiction > Educational
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