ECON2231 · Economics
Morrissey College of Arts & Sciences
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 specifics model to model the various types of time series include linear regression, panel regression, seasonal decomposition, exponential smoothing, ARIMA modeling as well as combining models. This course is offered as an online hybrid course. In addition to the online lectures presented on the Canvas LMS, there are three required on-campus class meetings on Saturday mornings.Please see the course syllabus for additional details.
Course experience
Averages use the original five-point historical evaluation scale.
Organization
3.8 / 5
How well the course was organized
Challenge
4.0 / 5
How intellectually challenging students found it
Attendance
3.7 / 5
How necessary attendance was
Assignments
4.0 / 5
How helpful assignments were
Weekly effort
~4
hours per week
Estimated from the original workload response buckets. Individual sections may differ.
Instructor options
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Across time
Section-level results available in the recovered archive.
Spring 2025
1 sectionFall 2024
1 sectionSpring 2024
1 sectionFall 2023
1 sectionSpring 2023
1 sectionFall 2022
1 sectionSpring 2022
1 section