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

Catalog description

Prerequisites: MATH 462 with a grade of C or better. This course is the continuation of MATH 462 . In this course, the following basic statistical learning objects will be reviewed: variable/model selection, support vector machine, tree-based methods, cluster analysis. Students will work in teams on real-world projects which will require extensive use of statistical software. Each group will produce a written report and give an oral presentation of their findings. present their work in a research talk. Successful completion of this course will equip students with the modern statistical learning, teamwork, and presentation skills necessary to conduct advanced research or enter the professional world.