George Mason University
George Mason University Mason
George Mason University

OR 568: Applied Predictive Analytics

Instructor Information

Section Information

Introduces predictive analytics with applications in engineering, business, and econometrics. Topics include time series and cross-sectional data processing, correlation, linear and multiple regressions, time series decomposition, predictive modeling and case study. Provides a foundation of basic theory and methodology with applied examples to analyze large engineering and econometric data for predictive decision making. Hand-on experiments with R will be emphasized.

Course Information from University Catalog

Not Repeatable


Introduces predictive analytics with applications in engineering, business, and econometrics. Topics include time series and cross-sectional data processing, correlation, linear and multiple regressions, time series decomposition, predictive modeling and case study. Provides a foundation of basic theory and methodology with applied examples to analyze large engineering and econometric data for predictive decision making. Hand-on experiments with R will be emphasized.

Hours of Lecture or Seminar per week: 3

Equivalent to SYST 568.

Credits: 3

Prerequisites:

STAT 515 or Graduate Standing at the MSOR or MSSE programs.

Instructor Information
Expertise