11| Question 2 | | | | | | The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods, and nondurable goods industries. Shown here are factory orders in the United States over a 13-year period ($ billion). | | | | | a. Use these data to develop forecasts for the years 6 through 13 using a 5-year moving average. | | | | | b. Use these data to develop forecasts for the years 6 through 13 using a 5-year weighted moving average. Weight the most recent year by 6, the previous year by 4, the year before that by 2, and the other years by 1. | | | | | c. Compute the errors of the forecasts in parts (a) and (b) and then the MAD. Which forecast is better? | | | | | | | | | | | YEAR | FACTORY ORDERS ($ billion) | | 1 | 2,512.70 | | 2 | 2,739.20 | | 3 | 2,874.90 | | 4 | 2,934.10 | | 5 | 2,865.70 | | 6 | 2,978.50 | | 7 | 3,092.40 | | 8 | 3,356.80 | | 9 | 3,607.60 | | 10 | 3,749.30 | | 11 | 3,952.00 | | 12 | 3,949.00 | 13| Question 3 | | | | | | The “Economic Report to the President of the United States” included data on the amounts of manufacturers’ new and un?lled orders in millions of dollars. Shown here are the ?gures for new orders over a 21-year period. Use Excel to develop a regression model to ?t the trend effects for these data. Use a linear model and then try a quadratic model. How well does either model ?t the data? | | | | | YEAR | TOTAL NUMBER OF NEW ORDERS | | 1 | 55,022 | | 2 | 55,921 | | 3 | 64,182 | | 4 | 76,003 | | 5 | 87,327 | | 6 | 85,139 | | 7 | 99,513 | | 8 | 115,109 | | 9 | 131,629 | | 10 | 147,604 | | 11 | 156,359 | | 12 | 168,025 | | 13 | 162,140 | | 14 | 175,451 | | 15 | 192,879 | | 16 | 195,706 | | 17 | 195,204 | | 18 | 209,389 | | 19 | 227,025 | | 20 | 240,758 | | 21 | 243,643 |
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guru2009
10 years ago
determine_the_error_for_each_of_the_following_forecasts.xlsx
