| summarize_normal_normal {bayesrules} | R Documentation | 
Summarize a Normal-Normal Bayesian model
Description
Consider a Normal-Normal Bayesian model for mean parameter \mu with 
a N(mean, sd^2) prior on \mu and a Normal likelihood for the data. 
Given information on the prior (mean and sd) 
and data (the sample size n, mean y_bar, and standard deviation sigma),
this function summarizes the mean, mode, and variance of the 
prior and posterior Normal models of \mu.
Usage
summarize_normal_normal(mean, sd, sigma = NULL, y_bar = NULL, n = NULL)
Arguments
| mean | mean of the Normal prior | 
| sd | standard deviation of the Normal prior | 
| sigma | standard deviation of the data, or likelihood standard deviation | 
| y_bar | sample mean of the data | 
| n | sample size of the data | 
Value
data frame
Examples
summarize_normal_normal(mean = 2.3, sd = 0.3, sigma = 5.1, y_bar = 128.5, n = 20)
[Package bayesrules version 0.0.2 Index]