3 credits
Spring 2026 Lecture Distance Learning Upper Division
An introduction to the mathematical theory of statistical inference, emphasizing inference for standard parametric families of distributions. Properties of estimators. Maximum likelihood estimation. Sufficient statistics. Hypothesis tests and confidence intervals. Distribution theory for common statistics based on normal distributions, including linear regression. Bayesian Statistics include posterior inference, posterior mean, maximum a-posteriori estimator, credible intervals, and Bayesian hypothesis testing.
Learning Outcomes1Understand and able to use inference for standard parametric families of distributions; properties of estimators; Bayes and maximum likelihood estimation; sufficient statistics; properties of test of hypotheses; distribution theory for common statistics based on normal distributions.
Prerequisites
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