ESE 531 - Statistical Learning and Inference

Minimum variance unbiased estimation, Cramer- Rao lower bounds, learning and inference with linear models, maximum likelihood estimation, least squares estimation, Bayesian inference, statistical decision theory, hypothesis testing with deterministic and random signals, composite hypothesis testing, model selection.

3 credits

Grading Letter graded (A, A-, B+, etc.)