BAN 673 - Time Series Analytics

Units: 3
Introduces fundamental concepts and methods of time series analytics. Topics include evaluation of data patterns, moving averages, smoothing models, regression-based forecasting, and ARIMA models. Emphasis is on hands-on experience in applying time series analytics in business.

Prerequisites: BAN 602.
Possible Instructional Methods: Entirely On-ground, or Hybrid.
Grading: A-F grading only.
Student Learning Outcomes - Upon successful completion of this course students will be able to:

Evaluate data patterns to select appropriate time series methods.
Recognize and utilize fundamental concepts and applications of time series analytics including moving averages, smoothing models, regression-based and ARIMA forecasting.
Identify efficient ways of applying time series analytics for business forecasting.