DataCamp

Approximating the likelihood function

The first election poll is in! X = 6 of 10 polled voters plan to vote for you. In the previous exercise you explored the dependence of X on your underlying support p. Specifically, you simulated one poll result X from each of 1,000 possible values of p between 0 to 1. Here you will restrict your attention to only those simulations that produced polls that match your data, X = 6. The corresponding collection of p from which these polls were generated will provide insight into which values of p are the most compatible with your observed poll data.

The likelihood_sim data frame containing the simulated polls for each p in p_grid is in your workspace.

Modify the density plot code. Supply a condition to fill that highlights the poll_result which matches your observed poll data, X = 6.
Using dplyr code, pipe (%>%) your likelihood_sim data into a filter() which keeps only the simulations in which the poll_result matches your poll data. To define this filter(), use the same condition you used to construct the density plot above.
Construct a density plot of the remaining p_grid values.

Take Hint (-30 XP)

Exercise

Approximating the likelihood function

Instructions