STAT 239 Regression Models
This course is an intermediate statistics course that focuses on fitting
statistical models to data . Students will learn how to pose a statistical question, perform
appropriate statistical analysis of the data, and properly interpret and communicate their results.
We will cover the following topics: designing experiments, permutation tests, bootstrap
confidence intervals, one- and two-way analysis of variance, chi-square tests, p-values, simple
and multiple regression modeling, model prediction, and goodness of fit. Extensive use is made
of the R programming language. Extensive use is made of the R statistical software.
Course Type
QL, HON