Interpreting the posterior

Recall that a Prior of (0.5, 0.5) reflected our prior opinions about the chance of Spinner A and Spinner B.

After observing a blue spin, the Bayes' rule calculations are summarized in the following data frame, bayes_df:

      Model Prior Likelihood    Product Posterior
1 Spinner A   0.5  0.5000000 0.25000000      0.75
2 Spinner B   0.5  0.1666667 0.08333333      0.25

You can use the function prior_post_plot() from the TeachBayes package to display the prior and posterior probabilities:

prior_post_plot(bayes_df)

Which statement reflects your current beliefs about the identity of the unknown spinner?

Spinners A and B are equally probable.

The unknown spinner is more likely to be Spinner A.

The unknown spinner is more likely to be Spinner B.

One cannot determine which spinner is more likely from these calculations.

Exercise