achievement

Achievement data for a group of Austrian school children

datasets

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

achievement function

A data frame with 109 observations on the following 7 variables.<dl class="dl-horizontal">
 <dt>Gen</dt><dd>gender of child where 0 is male and 1 is female</dd>
 <dt>Age</dt><dd>age in months</dd>
 <dt>IQ</dt><dd>iq score</dd>
 <dt>math1</dt><dd>test score on mathematics computation</dd>
 <dt>math2</dt><dd>test score on mathematics problem solving</dd>
 <dt>read1</dt><dd>test score on reading speed</dd>
 <dt>read2</dt><dd>test score on reading comprehension</dd>
 </dl>

Format

School achievement data — achievement

A data frame with 109 observations on the following 7 variables.<dl class='dl-horizontal'>
 <dt>Gen</dt><dd>gender of child where 0 is male and 1 is female</dd>
 <dt>Age</dt><dd>age in months</dd>
 <dt>IQ</dt><dd>iq score</dd>
 <dt>math1</dt><dd>test score on mathematics computation</dd>
 <dt>math2</dt><dd>test score on mathematics problem solving</dd>
 <dt>read1</dt><dd>test score on reading speed</dd>
 <dt>read2</dt><dd>test score on reading comprehension</dd>
 </dl>

achievement: School achievement data

Description

Usage

Arguments

Format