Course Description
Overview of data structures, data lifecycle, statistical inference. Data management, queries, data cleaning, data wrangling. Classification and prediction methods to include linear regression, logistic regression, k-nearest neighbors, classification and regression trees. Association analysis. Clustering methods. Emphasis on analyzing data, use and development of software tools, and comparing methods.
Fall 2025
Instructors
Meeting Patterns
Classes Start:
August 18, 2025
Classes End:
December 2, 2025
Location:
00315 Riddick Hall
Class Days:
T H
Class Start Time:
8:30am
Class End Time:
9:45am
Class Type:
Lecture
Credits:
3.00
Restrictions:
Prerequisite: (MA 305 or MA 405) and (ST 305 or ST 312 or ST 370 or ST 372 or ST 380) and (CSC 111 or CSC 112 or CSC 113 or CSC 114 or CSC 116 or ST 114 or ST 445)
