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Department of Statistics

STAT 513

513—Theory of Statistical Inference. (3) (Prereq: STAT 512 with a grade of C or higher) Hypothesis testing, Neyman-Pearson lemma, likelihood ratio tests, power, theory of linear models including multiple linear regression and ANOVA, Bayesian inferences, advanced topics including survival analysis.

Sample Course Homepage: Recent Semester, Another Recent Semester

Usually Offered: Fall Semesters

Purpose: To provide a strong foundation in mathematical development of statistical inference methodology.

Current Textbook: Mathematical Statistics with Applications (7th Ed.), D. Wackerly, W. Mendenhall and R. Sheaffer, Duxbury, 2008.


Topics Covered
Hypothesis testing: Type I/II Error, large-sample tests, power, Neyman- Pearson Lemma, uniformly most powerful tests, likelihood ratio tests.
4 weeks
Regression models: Simple and multiple linear regression models, least squares, sampling distributions, analysis of variance, F tests, confidence and prediction intervals.
3 weeks
Bayesian inference: Bayesian paradigm, prior model selection, posterior computation, point estimation, credible intervals.
3 weeks
Survival analysis: Censoring, hazard functions, life-table estimates, Kaplan-Meier estimator, two-sample (log-rank) tests, power and sample size, k-sample tests.
Supplementary Material
3 weeks

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: Karl GregoryJoshua Tebbs 

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