Lesson 8 builds a conjugate model for Poisson data and discusses strategies for selection of prior hyperparameters. Bayesian models, including admixture models, are a powerful framework for articulating complex assumptions about large-scale genetic data; such models are widely used to explore data or to study population-level statistics of interest. Suppose 50 field goals are attempted at a distance of 40 years. Lesson 6.2 Prior predictive: binomial example 5:20. Let \(y = (y_1, \dots, y_n)\) be the observed data. Note that the variational interpretation and the derivation of the objective function in this section corresponds to Bernoulli dropout, i.e. SR2 Chapter 3 Hard Posted on 5 April, 2020 by Brian Tags: statistical rethinking, solutions, grid approximation, posterior predictive check, posterior predictive distribution, map, binomial, hpdi Category: statistical-rethinking-2 Here’s my solutions to the hard exercises in chapter 3 of McElreath’s Statistical Rethinking, 2nd edition. In the above example: P −z α/2 < θ−µ 1 √ φ