Doing Bayesian data analysis [electronic resource] : a tutorial with R and BUGS / John K. Kruschke.

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Bibliographic Details
Published: Amsterdam ; Boston : Academic Press, c2011.
Online Access:
Main Author:
Kruschke, John K.
Subjects:
Bayesian statistical decision theory.
R (Computer program language)
Format: Electronic eBook
Doing Bayesian data analysis a tutorial with R and BUGS /
Table of Contents:
  • This book's organization : read me first!
  • Introduction : models we believe in
  • What is this stuff called probability?
  • Bayes' rule
  • Inferring a binomial proportion via exact mathematical analysis
  • Inferring a binomial proportion via grid approximation
  • Inferring a binomial proportion via the Metropolis algorithm
  • Inferring two binomial proportions via Gibbs sampling
  • Bernoulli likelihood with hierarchical prior
  • Hierarchical modeling and model comparison
  • Null hypothesis significance testing
  • Bayesian approaches to testing a point ("null") hypothesis
  • Goals, power, and sample size
  • Overview of the generalized linear model
  • Metric predicted variable on a single group
  • Metric predicted variable with one metric predictor
  • Metric predicted variable with multiple metric predictors
  • Metric predicted variable with one nominal predictor
  • Metric predicted variable with multiple nominal predictors
  • Dichotomous predicted variable
  • Ordinal predicted variable
  • Contingency table analysis
  • Tools in the trunk.

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