Statistics and Statistical Learning (Capstone I). 3 credits, 3 contact hours

Catalog description

Prerequisites: MATH 461 , MATH 478 with a grade of C or better. This is the first semester of a two-semester undergraduate-level statistical learning capstone course. The course provides an opportunity for students to synthesize knowledge gained during their undergraduate study by applying modern statistical tools to solve real-world projects. In this first semester course, the following basic statistical learning objects will be reviewed: statistical decision theory, linear/logistic regression, discriminant analysis, principle component analysis, high-dimensional data analysis, nearest neighbor methods, multiclass classification. The course will also select important papers on the above topics for students to read and present. Capstone research topics will be selected approaching the end of the semester.