MATH 316 - Statistical Learning with Applications

4 Hour(s) Credit
An introduction to statistical methods and models for data analysis with applications. Methods and models, such as regression models, time series models, principal components analysis, decision trees, cluster analysis and/or other selected topics, are studied, including the mathematics/statistics foundations and the applications of each method/model. R and Python are used as computational tools; select one of them to complete all assignments. Does not fulfill the math requirement for education majors.
Four hours per week
Prerequisites C or better in MATH 214 or MATH 216