Exercise

The posterior

In our spinner example, Prior contains the prior probabilities (1/2, 1/2) and Likelihood contains the likelihoods (1/2, 1/6) since the result of the spin was blue (3).

To compute the product and posterior probabilities, you can use the bayesian_crank() function, which takes as input a data frame containing Model, Prior and Likelihood.

Instructions

100 XP

The vector of models, Model, is available in your workspace.

Create the two vectors Prior and Likelihood using the values provided above.
Construct a data frame called bayes_df containing variables Model, Prior, and Likelihood, in that order.
Use the bayesian_crank() function to compute the posterior probabilities of Spinner A and Spinner B.