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STAT 4740: Introduction to Bayesian Data Analysis

(Dual-listed with STAT 5740).
Credits: 3. Contact Hours: Lecture 2, Laboratory 2.

Prereq: (STAT 3010 or STAT 3260 or STAT 4010 or STAT 5870); (STAT 3410 or STAT 3470 or STAT 4470 or STAT 5880)
Probability models and prior distributions; updating priors through the likelihood function. Computational and simulation-based methods for deriving posterior distributions and for estimating parameters. Basic statistical and hierarchical models. Model adequacy and posterior predictive checks. Markov Chain Monte Carlo methods and introduction to WinBUGS or similar software. Emphasis on applications and examples from the social, biological and physical sciences. Graduation Restriction: Credit for only one of STAT 4440, STAT 4740, or STAT 5740 may be applied to graduation. May not be used for graduate credit in the Statistics MS and PhD degree programs. (Typically Offered: Spring)

The curriculum in liberal arts and sciences with a major in statistics is designed to prepare students for (1) statistics positions in business, industry or commerce, nonprofit institutions, and in state or federal government; and (2) graduate study in statistics. Positions include the following types of work: statistical design, data visualization, analysis and interpretation of experiments and surveys; data processing and analysis using modern computation facilities and statistical computing systems; application of statistical principles and methods in commercial areas such as finance, insurance, industrial research, technology, marketing, manufacturing, sports analytics, quality control, and nonprofit organizations, such as institutions involved in health care or medical research.