Time Series Analysis and Forecasting

Andrei Volodin (University of Regina)

Sep 8, 2026 — Dec 22, 2026

About the course

This course aims to introduce various statistical models for time series and cover the main methods for analysis and forecasting. Topics include: Deterministic time series: Trends and Seasonality; Random walk models; Stationary time series: White noise processes, Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA) models; Estimation, Diagnosis and Forecasting with various time series models; computer programming for Time Series Analysis.

Registration

This course is available for registration under the Western Dean's Agreement. To register, you must obtain the approval of the course instructor and you must complete the Western Dean's agreement form , using the details below. The completed form should be signed by your home institution department and school of graduate studies, then returned to the host institution of the course.

Enrollment Details

Course Name
Econometric Models & Forecasts
Date
Sep 8, 2026 — Dec 22, 2026
Course Number
STAT 818
Section Number
001
Section Code
32873

Instructor(s)

For help with completing the Western Dean’s agreement form, please contact the graduate student program coordinator at your institution. For more information about the agreement, please see the Western Dean's Agreement website

Other Course Details

Class Schedule

Tuesday and Thursday 10:00 - 11:15 a.m. in CL 305 and remotely on Zoom (see syllabus)

There are 8 asynchronous computer labs, starting on Sept. 16

Office Hours

  • Wednesday 2:30pm-3:30pm or by an appointment

Please note that these times above are in the Saskatchewan timezone and that Saskatchewan doesn’t participate in daylight savings.

Remote Access

This will be a hybrid course delivered by Zoom. The instructor will share the existing electronic presentation and will use a laptop (or tablet), which can be shared electronically for some special notes during lectures.

Availability

This course may be open to students from universities outside of the PIMS network, and those coming from industry/government.

Grading

Your final grade will be calculated as follows:

  • Assignments 10%
  • Term project 10%
  • Computer Lab 15%
  • Midterm 20%
  • Final 45%
2026-2027