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.