From the course: Business Analytics: Forecasting with Seasonal Baseline Smoothing
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Simple seasonal indexes
From the course: Business Analytics: Forecasting with Seasonal Baseline Smoothing
Simple seasonal indexes
- [Instructor] I'm in exercise file 01_04 on the worksheet named Seasonal Effect Example. To build a forecast that responds to seasonality in the baseline we need to start by defining seasonal effects. A seasonal effect measures the amount of the effect that being in a given season exerts on values in the baseline. In this case, simply being in the season named December might increase the December sales by $10,000 over the average monthly sales for the year. Similarly, taking place in the month of July might decrease July sales by $3,000 below the average monthly sales for the year. Then the seasonal effect for December would be plus 10,000, and the seasonal effect for July would be minus 3,000. Let's see how that works out in practice. On the worksheet that you see, I have calculated the mean sales for the first year in cell M4. I gave the cell the name Year_1_Mean, as shown in cell L4. So the seasonal effect for the first period, in cell J2, subtracts the year one mean from the…
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