MATH 3150 - Applied Linear Models

3 Credit(s) | $3.75 Fee

Introduction to data analysis and applied statistical methods commonly used in industrial and scientific applications as well as in data science. Emphasis will be on the practical aspects of statistics with students analyzing real data sets. Topics covered include analytic and graphical representation of data, exploratory data analysis, one- and two-way ANOVA, post hoc tests, linear regression analysis, model diagnostics, and logistic regression. Optional topics include non-parametric tests, bootstrapping, and principal component analysis. Students will use R throughout the course. (Fall) [Graded Letter]

Prerequisite(s): ([MATH 1040 or MATH 1190 or MATH 3700] and [MATH 1050 or MATH 1100 or MATH 1210]) or instructor permission - Prerequisite Min. Grade: C