120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science
Coverage of the main parametric techniques used in statistical inference. Data reduction. Method of moments, maximum likelihood, and Bayesian point estimation. The Cramer-Rao inequality. Interval estimation. Pivotal quantities. Inversion methods. Principles of deriving tests. Neyman-Pearson lemma. Uniformly most powerful tests. Likelihood ratio tests. Large sample tests. Wald & score tests. Bayesian interval estimation and hypothesis testing.
