STA432
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Theory and Methods of Statistical Learning and Inference
Subject
STA
Catalog Number
432
Title
Theory and Methods of Statistical Learning and Inference
Course Description
Estimators and properties (efficiency, consistency, sufficiency); loss functions. Fisher information, asymptotic properties, and distributions of estimators. Exponential families. Point and interval estimation, delta method. Neyman-Pearson lemma; likelihood ratio tests; multiple testing; design and the analysis of variance (ANOVA). High-dimensional data; statistical regularization and sparsity; penalty and prior formulations; model selection. Resampling methods; principal component analysis, mixture models. Prerequisite: (Statistical Science 240L, 230, 230S, or 231) and (Mathematics 202, 212, 219, or 222). Not open to students with credit for STA 250.
Grading Basis
Graded
Consent (Permission Number)
No Special Consent Required
Min Units
1
Max Units
1
Lecture
Crosslisted Courses
General Education Curriculum Codes
(QS) Quantitative Studies