Exercise

Explore using the Beta distribution as a prior

The Beta distribution is a useful probability distribution when you want model uncertainty over a parameter bounded between 0 and 1. Here you'll explore how the two parameters of the Beta distribution determine its shape.

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One way to see how the shape parameters of the Beta distribution affect its shape is to generate a large number of random draws using the rbeta(n, shape1, shape2) function and visualize these as a histogram. The code to the right generates 1,000,000 draws from a Beta(1, 1) distribution: A Beta distribution with both shape parameters set to 1.

Visualize these draws using the hist function.