| summarize_normal_normal | 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)
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