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STAT 463 Fundamentals of Statistical Inference Units: 3.00
Decision theory and Bayesian inference; principles of optimal statistical procedures; maximum likelihood principle; large sample theory for maximum likelihood estimates; principles of hypotheses testing and the Neyman-Pearson theory; generalized likelihood ratio tests; the chi-square, t, F and other distributions.
Learning Hours: 132 (36 Lecture, 96 Private Study)
Course Equivalencies: STAT363; STAT463
Offering Faculty: Faculty of Arts and Science
Course Learning Outcomes:
- Derive properties of distributions; finding optimal estimators and tests.
- Develop a theoretical understanding of discrete and continuous random variables, distribution functions, sampling distributions, point estimation, interval estimation, hypothesis testing, large sample theory and basic Bayesian methods.
- Prove Rao-Blackwell theorem, Lehmann-Scheffe theorem, Neyman-Pearson lemma.