summarize_normal_normal {bayesrules} | R Documentation |
Consider a Normal-Normal Bayesian model for mean parameter μ with a N(mean, sd^2) prior on μ 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 μ.
summarize_normal_normal(mean, sd, sigma = NULL, y_bar = NULL, n = NULL)
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 |
data frame
summarize_normal_normal(mean = 2.3, sd = 0.3, sigma = 5.1, y_bar = 128.5, n = 20)