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Course Description

A layer of complexity can be added to forecasting in the form of seasonality, where the time series being studied regularly changes with each season. This added element must be considered in any prediction of future periods. In this lesson, you will define the factors that cause seasonality. You will identify the steps to follow in forecasting a seasonal time series, which include quantifying and separating seasonal influences and then applying that information to your forecasting. And you will follow those steps yourself in computing seasonal forecasts.

Benefits to the Learner

  • Define the factors that cause seasonality
  • Identify the steps to follow in forecasting a seasonal time series, which include quantifying and separating seasonal influences
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Type
self-paced (non-instructor led)
Dates
Aug 12, 2019 to Dec 31, 2030
Total Number of Hours
1.0
Course Fee(s)
Regular Price $0.00
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