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Chapter 8: Time Series and Forecasting The CSUSM Restaurant just finished its fourth year of operation. Through the great efforts of its manager and staff,

Chapter 8: Time Series and Forecasting The CSUSM Restaurant just finished its fourth year of operation. Through the great efforts of its manager and staff, this restaurant has become one of the most popular and fastest-growing restaurants in the SD County. The manager has recently decided to improve the capacity planning process of the restaurant. To do so, they need to come up with an effective forecasting procedure to predict the monthly sales of foods for up to a year in advance (12 months). Data file CH8 shows the value of food sales ($100s) for the first four years of operation. You, as the new forecasting analyst, have been asked to propose a new forecasting procedure with a summary of your method, forecasts, and recommendations. Include the followings: 3. Using dummy variables for seasonality effects, forecast sales for January through December of the fifth year. 4. Add a trend effect to your forecasting model in (3) and forecast sales for January through December of the fifth year again with the new model. 5. Which model is expected to give more accurate forecasts, (3) or (4)? Calculate MSE for both techniques. 6. Assume that restaurants sales in January of the fifth year turn out to be $175,000. What was your forecast (and what is the forecasting error)? How do you explain this error to the manager?

Month Sales
1 1331
2 1293
3 1276
4 979
5 1012
6 770
7 798
8 836
9 605
10 715
11 836
12 1133
13 1447
14 1309
15 1359
16 1062
17 1062
18 820
19 864
20 886
21 671
22 715
23 919
24 1265
25 1551
26 1403
27 1458
28 1128
29 1155
30 880
31 913
32 957
33 693
34 814
35 952
36 1293
37 1651
38 1513
39 1558
40 1228
41 1255
42 980
43 1013
44 1015
45 798
46 919
47 1052
48 1394

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