Explores statistical inference, sufficiency, and completeness, emphasizing the importance of sufficient statistics and the role of complete statistics in data reduction.
Explores Bayesian techniques for extreme value problems, including Markov Chain Monte Carlo and Bayesian inference, emphasizing the importance of prior information and the use of graphs.
Explores sufficient statistics, data compression, and their role in statistical inference, with examples like Bernoulli Trials and exponential families.
