1. Exercise 8.8 “Consider the weekly thermostat sales in Figure 8.7(b)” Data are in table 8.1 (p. 359) and can be found on the CDROM, e.g. as a Minitab Worksheet:

2. Weekly data (52 weeks). Seasonal variation? Could be if the sales depend on the weekday. Not reasonable for this type of good. (Figure out if there are other types of goods whose sales figures depend on the weekday) Here: Data possess a trend but no seasonal variation  Use Holt’s method for forecasting.

3. “a. Using the first 52 weeks of sales (that is, use T = 52), find the point forecast and 95% prediction interval för sales in week 56. b. Using the first 52 weeks of sales, find the point forecast and 95% prediction interval för sales in week 57. The trend seems to be a bit less stable while there are no obvious level shifts Gives forecasts for weeks 53, 54, 55, 56 and 57 of which the last two were asked for.

4. Double Exponential Smoothing for y Data y Length 52 Smoothing Constants Alpha (level) 0.2 Gamma (trend) 0.3 Accuracy Measures MAPE 10.437 MAD 22.531 MSD 821.958 Forecasts Period Forecast Lower Upper 53 316.067 260.866 371.267 54 318.982 261.158 376.806 55 321.897 261.197 382.598 56 324.813 261.016 388.609 57 327.728 260.647 394.809

5. Alt. Let Minitab optimize the smoothing parameters Smoothing Constants Alpha (level) 0.489596 Gamma (trend) 0.066912 Accuracy Measures MAPE 10.339 MAD 22.370 MSD 887.404 Forecasts Period Forecast Lower Upper 53 324.219 269.414 379.025 54 328.441 266.602 390.280 55 332.662 263.054 402.270 56 336.883 258.990 414.777 57 341.105 254.558 427.651 Compare with previous 56 324.813 261.016 388.609 57 327.728 260.647 394.809