Skip to main content

Seasonal Forecasting Methods MOOC 0130

Massive Open Online Courses Course

Course details

This course will enable you to forecast for trending and seasonal data in Excel. The Methods to be covered will be Holt's Method, Holt Winter's Method, Desasonalizing & Multiple Regression on Seasonal Data. The course provides the opportunity to use and evaluate current software. *Note: Thank you for your interest in a BCIT – Free Online Learning course. You are about to register for the course. If you are new to BCIT, you will first need to create a BCIT ID. Then, log in with your ID and password to register. Once registered, log in to with your BCIT email address and password to access your online course. If you are new to BCIT, it may take up to 24 hours for your course access to become active. Because these are not credited courses, and you are not paying a fee, there may be student resources you come across that you are not entitled to access. This would include Student Aid and other financial assistance. Enjoy your learning and we’re happy to support your lifelong learning journey.


  • A working knowledge of Microsoft Excel, a rudimentary knowledge of math and a rudimentary knowledge of stats (not necessary but recommended).





Course offerings

Spring/Summer 2023

Below is one offering of MOOC 0130 for the Spring/Summer 2023 term.

CRN 67827


Start any time

  • 52 weeks
  • CRN 67827
  • $0.00
Continuous Entry, Distance or Online

This is an online learning course. Start any time. You have 52 weeks from the date you register to complete this course.



Course outline

Course outline TBD — see Learning Outcomes in the interim.



Important information
  1. Internet delivery format.

Learning Outcomes

Upon successful completion of this course, the student will be able to:

  • Identify the 4 components of time series data
  • Identify seasonality in data
  • Learn how to perform Holt's Method for Trend
  • Learn how to perform Holt Winter's Method
  • Learn how to deseasonalize data
  • Learn how to create dummy variables
  • Use multiple regression & dummy variables to perform forecasts on seasonal data

Effective as of Spring/Summer 2021


Interested in being notified about future offerings of Seasonal Forecasting Methods (MOOC 0130)? If so, fill out the information below and we'll notify you by email when courses for each new term are displayed here.

  • Privacy Notice: The information you provide will be used to respond your request for BCIT course information and is collected under Section 26(c) of the Freedom of Information and Protection of Privacy Act (FIPPA). For more information about BCIT’s privacy practices contact: Associate Director, Privacy, Information Access & Policy Management, British Columbia Institute of Technology, 3700 Willingdon Ave. Burnaby, BC V5A 3H2, email: