An introduction to the concepts, theory, and application of statistical inference, including the structure of statistical problems, probability modeling, data analysis and statistical computing, and linear regression. Inference from the viewpoint of Bayesian statistics, with some discussion of sampling theory methods and comparative inference. Applications to problems in various fields. Instructor: Li, Tokdar, or Wolpert

Prerequisites: Math 202 or Math 212 or Math 222 AND Statistics 230 or Math 340.
Instructor: Wolpert, Robert
Time: M 1:25pm-2:40pm
Location: Old Chem 101