Statistical Inference: Model Selection and Nuisance Parameters

This lecture covers statistical inference topics such as model selection using the Kullback-Leibler divergence, the Akaike information criterion, and the network information criterion. It also discusses dealing with nuisance parameters, modified profile likelihoods, and higher-order inference methods.