BZAN6612 · Business Analytics
Carroll School of Management
The theory and practice of applied time series analysis will be explored. First the different segments (trend, seasonality, cyclical, and irregular) of a time series will be analyzed by examining the Autocorrelation functions (ACF) and Partial Autocorrelation functions (PACF). The various types of time series models include linear regression, panel regression, seasonal decomposition, exponential smoothing, and ARIMA modeling as well as combining models. In short, this course will equip you with tools necessary to construct forecasts to inform business decisions. As such, the focus of the course will not be only on tools, but also on how they are used in business. STEM-designated
Course experience
Averages use the original five-point historical evaluation scale.
Organization
3.4 / 5
How well the course was organized
Challenge
4.3 / 5
How intellectually challenging students found it
Attendance
4.3 / 5
How necessary attendance was
Assignments
4.0 / 5
How helpful assignments were
Weekly effort
~4.5
hours per week
Estimated from the original workload response buckets. Individual sections may differ.
Instructor options
Ratings below reflect only recovered evaluations connected to this course.
Across time
Section-level results available in the recovered archive.
Spring 2025
1 sectionSpring 2024
1 sectionSpring 2023
1 section