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

Format:

Book

Author/Creator:

Kruschke, John K.

Contributor:

Harry E. Humphreys Book Fund.

Language:

English

Subjects (All):

Bayesian statistical decision theory.

R (Computer program language).

Physical Description:

xvii, 653 pages : illustrations ; 25 cm

Place of Publication:

Burlington, MA : Academic Press, [2011]

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.

Notes:

Includes bibliographical references and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Harry E. Humphreys Book Fund.

ISBN:

0123814855

9780123814852

OCLC:

653121532

Publisher Number:

99949263393