There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data. The text delivers comprehensive coverage of all scenarios addressed by non-Bayesian textbooks--t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis).

This book is intended for first year graduate students or advanced undergraduates. It provides a bridge between undergraduate training and modern Bayesian methods for data analysis, which is becoming the accepted research standard. Prerequisite is knowledge of algebra and basic calculus. Free software now includes programs in JAGS, which runs on Macintosh, Linux, and Windows.

-Accessible, including the basics of essential concepts of probability and random sampling

-Examples with R programming language and BUGS software

-Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis).

-Coverage of experiment planning

-R and BUGS computer programming code on website

-Exercises have explicit purposes and guidelines for accomplishment

Similar Books

Mathematics

. PDF

Bayesian Data Analysis Andrew Gelman, John B. Carlin

Mathematics

. PDF

Bayesian Methods for Data Analysis, Third Edition Bradley P. Carlin

Mathematics

. PDF

Bayesian Analysis of Failure Time Data Using P-Splines Matthias Kaeding

Mathematics

. PDF

Missing Data in Longitudinal Studies Michael J. Daniels, Joseph W. Hogan

Mathematics

. PDF

Geometric Data Analysis Brigitte Le Roux

Mathematics

. PDF

Missing Data John W. Graham

Mathematics

. PDF

Introduction to Hierarchical Bayesian Modeling for Ecological Data Eric Parent, Etienne Rivot

Mathematics

. PDF

Handbook of Statistical Analysis and Data Mining Applications Robert Nisbet, John Elder

Mathematics

. PDF

Experiments with Mixtures - Third Edition John A. Cornell

Mathematics

. PDF

A Bayesian Analysis of QCD Sum Rules Philipp Gubler

Mathematics

. PDF

Bayesian Decision Analysis J. Q. Smith

Mathematics

. PDF

Bayesian Spectrum Analysis and Parameter Estimation G. Larry Bretthorst

Sign-Up as a Member and download as many E-Books as you want