Code for Discrete and Continuous

Python notebooks for all the computational examples about Discrete and Continuous from Chapter 6 of the book. See here for the full code repository.

Temperature and precipitation in Mauna Loa. Joint distribution of discrete and continuous variables, marginal distributions, conditional distributions, kernel density estimation
Height and sex. Mixture model, Gaussian parametric model, joint distribution of discrete and continuous variables, marginal distributions, conditional distributions
Height and handedness. Joint distribution of discrete and continuous variables, independence, kernel density estimation
Alzheimer’s diagnostics. Classification, Gaussian random vectors, Gaussian discriminant analysis, quadratic discriminant analysis, linear discriminant analysis, maximum likelihood, parametric models
Clustering according to height. Gaussian mixture model, expectation maximization algorithm, clustering, unsupervised learning
Clustering NBA players. Gaussian mixture model, expectation maximization algorithm, clustering, unsupervised learning
Election poll. Bayesian parametric modeling, beta distribution, prior and posterior distributions, conjugate prior
How not to predict an election. Bayesian parametric modeling, independence, conditional independence, Monte Carlo method