MATH 5660 - Statistical Data Analytics (3 Credit Hours)

Lecture Hours: 3 Lab Hours: 0
The course will apply concepts learned in diverse areas of mathematics to data analysis. Topics include clustering and classification, data cleaning, text analysis and document similarities, frequent itemsets and association rules, neural networks, support vector machines, and decision trees. This class has a primary focus on the underlying mathematical theory, with a secondary focus on application. Students will be introduced to R and RStudio for data storage, manipulation, and visualization.

Prerequisite(s): A minimum grade of “C” in all of the following: MATH 2160, MATH 2243, MATH 3337 or STAT 5531.
Cross Listing(s): MATH 5660G, STAT 5660, STAT 5660G.