Trend & Seasonal-Regression Technique

Trend & Seasonal-Regression Technique - Put cursor...

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Regression Technique With Dummy Variables for Trend Models With Seasonal Variation Situation: Model has been observed to have linear trend and 4-period seasonal variation over 20 periods. Required: Forecast for the next 4 periods (21-24) using regression. 1. Add n-1 dummy variables for the n-seasons. Since in this model there is 4-period seasonal variation add 3 dummy variables. The model is now y = β 0 + B 1 t + β 2 S 1 + β 3 S 2 + β 4 S 3 + ε, where S 1 , S 2 , and S 3 correspond to seasons 1, 2, and 3 respectively. For data from Season 1: Enter S 1 = 1 S 2 = 0 S 3 = 0. For data from Season 2: Enter S 1 = 0 S 2 = 1 S 3 = 0. For data from Season 3: Enter S 1 = 0 S 2 = 0 S 3 = 1. For data from Season 4: Enter S 1 = 0 S 2 = 0 S 3 = 0. 1. Enter dummy variable values in C2:D5 2. Highlight C2:D5 and COPY Put cursor in C6: PASTE Put cursor in C10: PASTE
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Unformatted text preview: Put cursor in C14: PASTE Put cursor in C18: PASTE 2. Move Column B in front of column A (if necessary) so that Period and Seasons columns are next to each other. 3. Highlight B1:B25 Select: CUT 4. Right Mouse Click on cell A1 Select: INSERT CUT 3. Perform Regression on Values vs. Period, S 1 , S 2 and S 3 . RESULT 5. Fill in Regression dialogue box 4. Do forecast. NOTES: 1. In this case, MMULT (row, column) is equivalent to SUMPRODUCT. SUMPRODUCT, however, requires both entries be rows or both entries be columns. 2. Check to see if all p-values for the period and seasons are low. If not, a modified F-test can be performed to determine if seasonal variables should be included. 6. In cell F22 enter: =$H$17+ 7. Drag F22 to F23:F25...
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