Need help with this question. Number 24 . I keep trying to figure it out and have been struggling please make document

w O CO O LO W N Month 397 476 397 472 385 EP - 37 Sales 254 212 168 200 180 143 TABLE 8. 3 | EP - 37 SALES AND LEASE DATA 132 80 Leases 147 138 126 ELL 120 D in W Month m 00 34 28 ~ EP - 37 Sales 1 , 296 1 , 267 1 , 199 1, 499 1 , 489 1 , 370 1 , 300 1, 669 1 , 603 1 , 716 1, 812 1, 817 1, 798 Leases 281 298 374 323 309 343 357 353 360 386 370 389 399 \\) = Difficult PM)independent Valle ( i.e., * = 1 for year 1 , * = 2 for year s , and so on In The year until * = 5 for year 5 ) . C. Forecast the annual sales for year b by using the regression model you developed in part ( b ) . `. Prepare the seasonal forecast for each month by using the monthly seasonal indices calculated in part (a)` 24 . The Midwest Computer Company serves a large number \\) of businesses in the Great Lakes region . The company sells supplies and replacements and performs service on all computers sold through seven sales offices. Many items are stocked , so close inventory control is necessam to assure customers of efficient service . Recently . business has been increasing , and management is con- cerned about stockouts . A forecasting method is needed to estimate requirements several months in advance so that adequate replenishment quantities can be pur- chased . An example of the sales growth experienced during the last 50 months is the growth in demand for item EP - 37 , a laser printer cartridge , shown in Table 8. 3. 2 . Develop a trend projection with regression solution using OM Explorer . Forecast demand for month 51 . b . A consultant to Midwest's management suggested that new office building leases would be a good leading indicator for company sales . The consultant quoted a recent university study finding that new office building leases precede office equipment and supply sales by 3 months . According to the study findings , leases in month 1 would affect sales in month 4 , leases in month 2 would affect sales in month 5 , and so on . Use POM for Windows' linear regression module to develop a forecasting model