Exercise

Updating by Bayes' rule

Good work!

The vector times contains ten reaction time measurements. These times are assumed to be a sample from a normal curve with mean M and standard deviation s = 20 milliseconds. For these data, \(\bar y = 275.9\) and \(se = 6.32\).

In the editor, the vectors M, Prior, times, and constants ybar, se are defined.

Instructions

100 XP

Use the dnorm() function to compute the likelihoods.
Create a data frame bayes_df containing M, Prior, and Likelihood.
Compute the posterior probabilities using the bayesian_crank() function and save the result back to bayes_df.
Use the prior_post_plot() function to compare the prior and posterior probabilities for M.

Take Hint (-30 XP)