Doing Bayesian Data Analysis

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  • Publisher : Academic Press
  • Release : 11 November 2014
  • ISBN : 9780124059160
  • Page : 776 pages
  • Rating : 5/5 from 2 voters

Doing Bayesian Data Analysis Book PDF summary

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 step-by-step 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 high-level 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 metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year 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 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 JAGS computer programming code on website Exercises have explicit purposes and guidelines for accomplishment Provides step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs

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Doing Bayesian Data Analysis

Doing Bayesian Data Analysis
  • Author : John Kruschke
  • Publisher : Academic Press
  • Release Date : 2014-11-11
  • ISBN : 9780124059160
DOWNLOAD BOOKDoing Bayesian Data Analysis

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 step-by-step 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,

Doing Bayesian Data Analysis

Doing Bayesian Data Analysis
  • Author : John Kruschke
  • Publisher : Academic Press
  • Release Date : 2010-11-25
  • ISBN : 0123814863
DOWNLOAD BOOKDoing Bayesian Data Analysis

There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and ‘rusty’ calculus. Unlike other textbooks, this book begins with the basics, including essential

Doing Bayesian Data Analysis

Doing Bayesian Data Analysis
  • Author : John K. Kruschke
  • Publisher : Academic Press
  • Release Date : 2014-11-03
  • ISBN : 0124058884
DOWNLOAD BOOKDoing Bayesian Data Analysis

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.

Bayesian Data Analysis, Third Edition

Bayesian Data Analysis, Third Edition
  • Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
  • Publisher : CRC Press
  • Release Date : 2013-11-01
  • ISBN : 9781439840955
DOWNLOAD BOOKBayesian Data Analysis, Third Edition

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. Throughout the text, numerous worked examples drawn from real applications and research emphasize the

Bayesian Analysis with Python

Bayesian Analysis with Python
  • Author : Osvaldo Martin
  • Publisher : Packt Publishing Ltd
  • Release Date : 2016-11-25
  • ISBN : 9781785889851
DOWNLOAD BOOKBayesian Analysis with Python

Unleash the power and flexibility of the Bayesian framework About This Book Simplify the Bayes process for solving complex statistical problems using Python; Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems and practice exercises; Learn how and when to use Bayesian analysis in your applications with this guide. Who This Book Is For Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement

Bayesian Statistics for Beginners

Bayesian Statistics for Beginners
  • Author : Therese M. Donovan,Ruth M. Mickey
  • Publisher : Oxford University Press, USA
  • Release Date : 2019
  • ISBN : 9780198841296
DOWNLOAD BOOKBayesian Statistics for Beginners

This is an entry-level book on Bayesian statistics written in a casual, and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary, notation, and understanding of the calculations used in many Bayesian problems.

A Student’s Guide to Bayesian Statistics

A Student’s Guide to Bayesian Statistics
  • Author : Ben Lambert
  • Publisher : SAGE
  • Release Date : 2018-04-20
  • ISBN : 9781526418265
DOWNLOAD BOOKA Student’s Guide to Bayesian Statistics

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics. Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers. Through a logical structure that introduces and builds upon key concepts in a gradual way and slowly acclimatizes students to using R and

Bayesian Data Analysis, Second Edition

Bayesian Data Analysis, Second Edition
  • Author : Andrew Gelman,John B. Carlin,Hal S. Stern,Donald B. Rubin
  • Publisher : CRC Press
  • Release Date : 2003-07-29
  • ISBN : 9781420057294
DOWNLOAD BOOKBayesian Data Analysis, Second Edition

Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include: Stronger focus on MCMC Revision of the computational

Statistical Rethinking

Statistical Rethinking
  • Author : Richard McElreath
  • Publisher : CRC Press
  • Release Date : 2018-01-03
  • ISBN : 9781315362618
DOWNLOAD BOOKStatistical Rethinking

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 model-based statistics, the book pushes readers to perform step-by-step 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

Bayesian Statistics the Fun Way

Bayesian Statistics the Fun Way
  • Author : Will Kurt
  • Publisher : No Starch Press
  • Release Date : 2019-07-16
  • ISBN : 9781593279578
DOWNLOAD BOOKBayesian Statistics the Fun Way

Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how

A First Course in Bayesian Statistical Methods

A First Course in Bayesian Statistical Methods
  • Author : Peter D. Hoff
  • Publisher : Springer Science & Business Media
  • Release Date : 2009-06-02
  • ISBN : 9780387924076
DOWNLOAD BOOKA First Course in Bayesian Statistical Methods

A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material. Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves. The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods.

Bayesian Essentials with R

Bayesian Essentials with R
  • Author : Jean-Michel Marin,Christian P. Robert
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-10-28
  • ISBN : 9781461486879
DOWNLOAD BOOKBayesian Essentials with R

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications. Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. Special attention is paid to the derivation of prior distributions in each

Data Analysis

Data Analysis
  • Author : Devinderjit Sivia,John Skilling
  • Publisher : OUP Oxford
  • Release Date : 2006-06-02
  • ISBN : 9780191546709
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One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. - Katie St. Clair MAA Reviews.

Bayesian Analysis for the Social Sciences

Bayesian Analysis for the Social Sciences
  • Author : Simon Jackman
  • Publisher : John Wiley & Sons
  • Release Date : 2009-10-27
  • ISBN : 0470686634
DOWNLOAD BOOKBayesian Analysis for the Social Sciences

Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan
  • Author : Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt
  • Publisher : Academic Press
  • Release Date : 2015-04-04
  • ISBN : 9780128016787
DOWNLOAD BOOKBayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces