MBA 551
Predictive Analytics for Business and Big Data
Section: 301

Course Description

This course is designed around the full analytics lifecycle which encompasses the business problem, the data, the analysis, and the decision. Students will learn to identify and clearly explain business problems that can be addressed with analytics. They will learn to determine which analytic methods are best suited to solve particular problems and clearly explain the results of an analytic model and how those results might impact the business bottom line. Analytical methods to be covered include data, visualization, a review of regression analysis; logistic regression; classification and regression trees (including boosting and bagging methodologies); and clustering (segmentation) methods. Students will also develop at least a beginning proficiency with several statistical software packages including Tableau, JMP, R, and SAS Enterprise Miner. Emphasis will be placed on analyzing real data and understanding how analytical thinking can be applied to solve big data problems.

Non-Std Tm

Through Fall 2027

Spring 2026

Instructors

Meeting Patterns

Classes Start:
January 24, 2026
Classes End:
January 24, 2026
Location:
01120 Nelson Hall
Class Days:
S
Class Start Time:
8:30am
Class End Time:
12:30pm

Classes Start:
February 21, 2026
Classes End:
February 21, 2026
Location:
01120 Nelson Hall
Class Days:
S
Class Start Time:
8:30am
Class End Time:
12:30pm

Classes Start:
March 28, 2026
Classes End:
March 28, 2026
Location:
01120 Nelson Hall
Class Days:
S
Class Start Time:
8:30am
Class End Time:
12:30pm

Classes Start:
April 18, 2026
Classes End:
April 18, 2026
Location:
01120 Nelson Hall
Class Days:
S
Class Start Time:
8:30am
Class End Time:
12:30pm

Classes Start:
January 12, 2026
Classes End:
April 28, 2026
Location:
Hybrid - Online and In-Person
Class Days:
[TBA]

Class Type:
Lecture
Credits:
3.00
Restrictions:
Prerequisites: MBA 506 and MBA 507 Master of Business Administration Majors Only