How to forecast the demand from 1/1/2022 to 12/1/2022 using the regression equation in excel? 5 L

How to forecast the demand from 1/1/2022 to 12/1/2022 using the regression equation in excel?

 

 

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5 L Home Insert Draw Page Layout X 1 2 3 4 D7 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 AutoSave OFF 20 Paste B A Month A 1/1/19 2/1/19 3/1/19 4/1/19 5/1/19 6/1/19 7/1/19 8/1/19 9/1/19 10/1/19 11/1/19 12/1/19 1/1/20 2/1/20 3/1/20 4/1/20 5/1/20 6/1/20 7/1/20 8/1/20 9/1/20 10/1/20 11/1/20 12/1/20 1/1/21 2/1/21 3/1/21 4/1/21 5/1/21 6/1/21 7/1/21 8/1/21 9/1/21 10/1/21 11/1/21 12/1/21 1/1/77 Calibri (Body) BIU X fx =B7/C7 Demand B 2272 2416 2893 2798 2401 3494 2581 2241 2279 2633 3482 4038 2603 2455 2533 3117 3567 3447 2449 2825 2857 3427 4174 5141 2660 2851 2894 3584 3707 3943 2954 3368 3476 4488 5226 6300 Financial information. 11 Formulas Data Review - A^ A V A Yearly average == = = = 2794 2794 2794 2794 2794 2794 2794 2794 2794 2794 2794 2794 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 SI and regression Pt 1 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 D Seasonal Index View 207 0.8132 0.8647 1.0354 1.0014 0.8593 1.2505 0.9238 0.8021 0.8157 0.9424 1.2462 1.4452 0.8093 0.7633 0.7876 0.9691 1.1091 1.0717 0.7614 0.8784 0.8883 1.0655 1.2978 1.5984 0.7023 0.7527 0.7641 0.9462 0.9787 1.0410 0.7799 0.8892 0.9177 1.1849 1.3798 1.6633 Data Mining ab Wrap Text Average SI Current operations Pt2 & Pt3 Merge & Center v E TemplateV7 (1) Tell me Number $ % 9 V F Deseasonalized Franchise operations Pt2 & Pt3 .00 00 0 Conditional Format. Cell Formatting as Table Styles G Time period Expected Values Pt3 H + NO Insert v Delete Format v Deseasonalized forecast Dv 27.0 Sort & Find & Filter Select 1 0 CLICK CELL J2 as output cell for regression Use the average seasonal Index in the column for 2019 Seasonalized forecast 67 Share Lad Analyze Data - Comments Sensitivity J + 110% K Regression Outp 5 L Home Insert Draw Page Layout X 1 2 3 4 D7 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 AutoSave OFF 20 Paste B A Month A 1/1/19 2/1/19 3/1/19 4/1/19 5/1/19 6/1/19 7/1/19 8/1/19 9/1/19 10/1/19 11/1/19 12/1/19 1/1/20 2/1/20 3/1/20 4/1/20 5/1/20 6/1/20 7/1/20 8/1/20 9/1/20 10/1/20 11/1/20 12/1/20 1/1/21 2/1/21 3/1/21 4/1/21 5/1/21 6/1/21 7/1/21 8/1/21 9/1/21 10/1/21 11/1/21 12/1/21 1/1/77 Calibri (Body) BIU X fx =B7/C7 Demand B 2272 2416 2893 2798 2401 3494 2581 2241 2279 2633 3482 4038 2603 2455 2533 3117 3567 3447 2449 2825 2857 3427 4174 5141 2660 2851 2894 3584 3707 3943 2954 3368 3476 4488 5226 6300 Financial information. 11 Formulas Data Review - A^ A V A Yearly average == = = = 2794 2794 2794 2794 2794 2794 2794 2794 2794 2794 2794 2794 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 3216.25 SI and regression Pt 1 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 3787.5833 D Seasonal Index View 207 0.8132 0.8647 1.0354 1.0014 0.8593 1.2505 0.9238 0.8021 0.8157 0.9424 1.2462 1.4452 0.8093 0.7633 0.7876 0.9691 1.1091 1.0717 0.7614 0.8784 0.8883 1.0655 1.2978 1.5984 0.7023 0.7527 0.7641 0.9462 0.9787 1.0410 0.7799 0.8892 0.9177 1.1849 1.3798 1.6633 Data Mining ab Wrap Text Average SI Current operations Pt2 & Pt3 Merge & Center v E TemplateV7 (1) Tell me Number $ % 9 V F Deseasonalized Franchise operations Pt2 & Pt3 .00 00 0 Conditional Format. Cell Formatting as Table Styles G Time period Expected Values Pt3 H + NO Insert v Delete Format v Deseasonalized forecast Dv 27.0 Sort & Find & Filter Select 1 0 CLICK CELL J2 as output cell for regression Use the average seasonal Index in the column for 2019 Seasonalized forecast 67 Share Lad Analyze Data - Comments Sensitivity J + 110% K Regression Outp

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To forecast the demand from 112022 to 1212022 using a regression equation in Excel you would typically follow these steps 1 Gather and Prepare Data En... View the full answer