In Part II of this series, we cover the elements of statistical modeling, focusing on:validation methodology principles of object-oriented design linear and logistic regression generalized linear models causality time series analysis Bayesian statistics, including simulations in pymc3 Modeling customer lifetime values, including a detailed study of the beta-Bernoulli/beta-binomial model, a discretized version of the classic Pareto/NBD an introduction to credibility theory The theory is illustrated with simulations in Python throughout the text.