Explores sufficient statistics, data compression, and their role in statistical inference, with examples like Bernoulli Trials and exponential families.
Introduces Bayesian estimation, covering classical versus Bayesian inference, conjugate priors, MCMC methods, and practical examples like temperature estimation and choice modeling.
