- International Fees
International fees are typically three times the amount of domestic fees. Exact cost will be calculated upon completion of registration.
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 learn.bcit.ca 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).
Below is one offering of MOOC 0130 for the Winter 2024 term.
Start any time
- 52 weeks
- CRN 89437
- Domestic fees $0.00International fees are typically three times the amount of domestic fees.
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 TBD — see Learning Outcomes in the interim.
- Internet delivery format.
- International fees are typically three times the amount of domestic fees. Exact cost will be calculated upon completion of registration.
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.
Programs and courses are subject to change without notice.