6. Using the trend adjusted model above, with the alpha and beta values provided, develop a forecast for period 28.

7. Using the data in the model, develop a six period moving average for period 26.

8. Using the data in the model, develop a forecast for period 27 using a weighted moving average model with weights of 0.5, 0.2, 0.2, 0.1 (with the first weight on the most recent data).

9. Develop a tracking signal, based on periods 13 through 16.

10. Based on your tracking signal, the model appears to track the data:

A. poorly

B. okay

C. Indicates nothing about the models tracking.,

Alpha .20 Beta .30 t Data % error 1 2 AN Smoothed 1,140.0 1,156.8 1,174.8 1,183.2 1,201.4 1,228.0 1,164 1,186 1,152 1,219 1,272 1,221 1,163 1,136 1,127 1,168 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Trend Forecast 15.0 15.5 1,155 16.3 1,172 13.9 1,191 15.2 1,197 18.6 1,217 17.2 1,247 11.4 1,259 4.5 1,251 -2.0 1,232 -4.4 -4.7 1,196 -5.4 1,191 -8.3 1,183 1,165 -16.8 1,158 -22.9 1,112 -27.7 1,068 -22.9 1,025 -17.7 1,018 -12.7 1,018 -10.4 1,021 -7.3 -3.8 1,239.8 1,228.0 1,211.0 1,200.8 1,195.4 1,188.4 1,173.2 1,166.2 1,128.6 1,091.4 1,052.6 1,041.0 1,035.4 1,034.2 1,029.4 1,029.2 1,033.6 0.8 1.2 -3.4 1.8 4.3 -2.1 -8.3 -10.1 -9.3 -3.5 -0.3 -1.1 -4.3 0.5 - 14.5 -10.2 -7.8 7.2 7.9 1,178 1,134 1,171 1,011 1,009 991 1,105 1,105 1,099 1,063 1,070 1,080 1,106 23 24