2009 Fall STA 114-001
Bulletin Course Description 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: Wolpert
(Instructor named in bulletin description above may not be current. For current instructor, see listing below.)
Title STATISTICS Department STA Course Number 2009 Fall 114 Section Number 001 Primary Instructor Wolpert,Robert L Prerequisites
Synopsis of course content
An introduction to the theory, concepts and application of modern statistical inference. Topics include the basic structure of statistical problems, probability modelling and statistical inference, and elements of data analysis, statistical computing, and linear regression. Likelihood-based inference is developed from both the modern Bayesian perspective and also from the sampling theory approach. This is the second semester of a two-semester sequence in probability and statistics. It is strongly
recommended that students take the prerequisite Probability course (STA 104/MTH 135) in the semester directly preceding STA 114
Additional Information
This course is cross-listed as Math 136.
