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. Prerequisite: Mathematics 202, 212, or 222, and Statistical Science 230 or Mathematics 340. NOTE: Effective Summer 2020, STA 250 has been replaced in the STA curriculum by STA 432/MATH 343.