Aug 11, 2020  
Undergraduate Catalog 2016-2017 
Undergraduate Catalog 2016-2017 [ARCHIVED CATALOG]

STAT 31900 - Bayesian Statistical Inference in the Sciences


Fundamental principles and techniques of probability, statistical inference and data analysis, as pertains to the sciences, especially bioinformatics.  Random variables and their distributions.  Central limit theorem.  Conditional probability, Markov chains and Hidden Markov Models.  Bayesian statistical paradigm and inference using Markov chain Monte Carlo. Computer simulations and data analysis.
prereq: MATH 15500; at least one of STAT 21200, STAT 21300 or STAT 21400 (or permission of instructor). Prerequisites waived for students who have passed STAT 311.
Familiarity with matrix algebra (at the level of MATH 160) and with the Windows computing environment are encouraged.

3 hrs
3 cr