Course Description
Pre-Requisite(s):
A previous statistics course, a previous linear algebra course, and permission of instructor
An introduction to linear statistical models in the context of data science. Topics include simple and multiple linear regression, generalized linear models, time series, analysis of covariance, tree-based classification, and principal components. The primary software is R.
