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  3. Bayesian Data Analysis in Python

Exercise

Analyzing regression parameters

Your linear regression model has four parameters: the intercept, the impact of clothes ads, the impact of sneakers ads, and the variance. The draws from their respective posterior distributions have been sampled for you and are available as intercept_draws, clothes_draws, sneakers_draws, and sd_draws, respectively.

Before you make predictions with your model, it's a good practice to analyze the posterior draws visually. In this exercise, you will first take a look at the descriptive statistics for each parameter's draws, and then you will visualize the posterior distribution for one of them as an example. pymc3 and pandas have been imported for you as pm and pd, respectively. Let's take a look at the parameters draws!

Instructions 1/3

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  • Create a DataFrame posterior_draws_df with four columns, each containing one parameter's posterior draws.