Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: Masters status in the School of Business OR Instructor Consent.
Description
This is a graduate level course in statistics, with an emphasis on developing predictive models using an open source statistical programming language. The engaged student should expect to develop foundational skills for data analysis. Topics covered will include some or all of the following: descriptive statistics, non-parametric regression, probability distributions, linear and logistic regression, tree-based methods, model assumptions and model checking, cross-validation, simulation, resampling, visualization, and reproducible research.