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Course Description

There are a number of time series that may require forecasting but do not have any discernible trend, such as a stable product environment or a very short timeframe. In this lesson, you will continue your look at forecasting by examining stationary time series and the situations in which they most often occur. You will also define autocorrelation and the key role that it plays in forecasting stationary data. Finally, you will practice forecasting techniques and stationary time series analysis.

Benefits to the Learner

  • Examine stationary time series and the situations in which they most often occur.
  • Define autocorrelation and the key role that it plays in forecasting stationary data
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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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