Problem 1Problem 1 (Note Use sheet called sales)Compute the forecast of the given sales projections (quarterly) using the following forecasting methods:a.) 3 month moving average...

This math is based on forecasting. Three problems in a different sheet. Data are attached with the following sheet of the problem. so problems are in seperate sheet.


Problem 1 Problem 1 (Note Use sheet called sales) Compute the forecast of the given sales projections (quarterly) using the following forecasting methods: a.) 3 month moving average forecast b.) 5 month moving average forecast c.) weighted moving average forecast with the given weights 0.5 (most recent), 0.3, and 0.2 d.) exponential smoothing with an alpha weight of .75 Compute the Mean Absolute Deviation/Error (MAD/MAE) for each forecasting method. Which is the better forecast method? Sales YearQuarterSales 11144 2151 3134 4151 21145 2145 3141 4166 31151 2164 3151 4176 41170 2180 3156 4187 51166 2182 3154 4169 Problem 2 Problem 2 (Note use sheet called Sales+) Given sales projections (quarterly) for 4 straight years and the advertising costs for the same periods. Compute a linear regression model and determine if is a good model/fit. Support your determination using available good fit testing. Sales + YearQuarterSalesAdvertising3 months5 months3months weighExp smooth3months error5months error3month weighted errorExp smooth error 1114441 215151 313432 415145 2114548 214534 314129 416643 3115140 216451 315139 417654 4117041 218052 315648 418747 5116644 218248 315444 416936 Problem 3 Problelm 3 (NOTE: Use 2 sheets titles county (Table 2) and carlson (Table 1)) FORECASTING LOST SALES The Carlson Department Store suffered heavy damage when a hurricane struck on August 31, 2000. The store was closed for four months (September 2000 through December 2000), and Carlson is now involved in a dispute with its insurance company about the amount of lost sales during the time the store was closed. Two key issues must be resolved: (1) the amount of sales Carlson would have made if the hurricane had not struck and (2) whether Carlson is entitled to any compensation for excess sales due to increased business activity after the storm. More than $8 billion in federal disaster relief and insurance money came into the county, resulting in increased sales at department stores and numerous other businesses. Table 1 gives Carlson's sales data for the 48 months preceding the storm. Table 2 reports total sales for the 48 months preceding the storm for all department stores in the county, as well as the total sales in the county for the four months the Carlson Department Store was closed. Carlson's managers have asked you to analyze these data and develop estimates of the lost sales at the Carlson Department Store for the months of September through December 2000. They also have asked you to determine whether a case can be made for excess storm-related sales during the same period. If such a case can be made, Carlson is entitled to compensation for excess sales it would have earned in addition to ordinary sales. Table1. Carlson’s Sales. Table 2. Department Store Sales. Managerial Report. Prepare a report for the managers of the Carlson Department Store that summarizes your findings, forecasts, and recommendations. Include: 1. An estimate of sales had there been no hurricane. 2. An estimate of countywide department store sales had there been no hurricane. 3. An estimate of lost sales for the Carlson Department Store for September through December 2000. In addition, use the countywide actual department stores sales for September through: December 2000 and the estimate in part (2) to make a case for or against excess storm related sales. county county sales 55.8 56.4 71.4 117.6 46.8 48 60 57.6 61.8 58.2 56.4 63 57.6 53.4 71.4 114 46.8 48.6 59.4 58.2 60.6 55.2 51 58.8 49.8 54.6 65.4 102 43.8 45.6 57.6 53.4 56.4 52.8 54 60.6 47.4 54.6 67.8 100.2 48 51.6 57.6 58.2 60 57 57.6 61.8 69 75 85.2 121.8 carlson sales 1.71 1.9 2.74 4.2 1.45 1.8 2.03 1.99 2.32 2.2 2.13 2.43 1.9 2.13 2.56 4.16 2.31 1.89 2.02 2.23 2.39 2.14 2.27 2.21 1.89 2.29 2.83 4.04 2.31 1.99 2.42 2.45 2.57 2.42 2.4 2.5 2.09 2.54 2.97 4.35 2.56 2.28 2.69 2.48 2.73 2.37 2.31 2.23