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Doing Bayesian Data Analysis: A Tutorial Introduction with R

Doing Bayesian Data Analysis: A Tutorial Introduction with R


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About the Book

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. Author website: http: //www.indiana.edu/ kruschke/DoingBayesianDataAnalysis/ -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

Review :
I think it fills a gaping hole in what is currently available, and will serve to create its own market as researchers and their students transition towards the routine application of Bayesian statistical methods.? -Prof. Michael lee, University of California, Irvine, and president of the Society for Mathematical Psychology Kruschke s text covers a much broader range of traditional experimental designs has the potential to change the way most cognitive scientists and experimental psychologists approach the planning and analysis of their experiments" -Prof. Geoffrey Iverson, University of California, Irvine, and past president of the Society for Mathematical Psychology John Kruschke has written a book on Statistics. It s better than others for reasons stylistic. It also is better because itis Bayesian. To find out why, buy it -- it s truly amazin !?-James L. (Jay) McClelland, Lucie Stern Professor & Chair, Dept. Of Psychology, Standford University


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Product Details
  • ISBN-13: 9780123814869
  • Publisher: Elsevier Science Publishing Co Inc
  • Publisher Imprint: Elsevier Science Publishing Co Inc
  • Language: English
  • Sub Title: A Tutorial Introduction with R
  • ISBN-10: 0123814863
  • Publisher Date: 25 Nov 2010
  • Binding: Digital (delivered electronically)
  • No of Pages: 672


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