Deseasonalizing Forecasts
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The document discusses seasonal adjustment methods for time series forecasts. It defines seasonality and explains common causes of seasonal patterns. The main seasonal adjustment method described is a four-step process: 1) forecast demand values, 2) calculate demand/forecast ratios, 3) average ratios to determine seasonal indices, 4) adjust forecasts by multiplying them by seasonal indices. An example is provided to illustrate applying this method to quarterly widget demand data.
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Deseasonalizing Forecasts
- 15. Seasonal Adjustments Example - Step 4
- 18. Exercise Table Click here to check your answer
- 21. Appendix A: Solution to Exercise
- 22. Appendix A: Solution to Exercise
Hinweis der Redaktion
- The following presentation is meant to familiarize individuals with methods of deseasonalizing forecasts. The most simple method of dealing with seasonality is discussed, and an example is provided. Prior knowledge of basic linear regression is assumed. If you have questions, you may contact the creator: Aaron Hirst [email_address]