Which one of the following statements about forecasting is FALSE? A. You should use the simple moving average method to estimate the mean demand of a time series that has a pronounced trend and seasonal influences. B. The weighted moving average method allows forecasters to emphasize recent demand over earlier demand. The forecast will be more responsive to change in the underlying average of the demand series. C. The most frequently used time-series forecasting method is exponential smoothing because of its simplicity and the small amount of data needed to support it. D. In exponential smoothing, higher values place greater weight on earlier demands in computing the average. E. When a significant trend exists, regression method may be effective. O A, B and E O A, D and E O A and D O C, D and E

Which one of the following statements about forecasting is FALSE? A. You should use the simple moving average method to estimate the mean demand of a time series that has a pronounced trend and seasonal influences. B. The weighted moving average method allows forecasters to emphasize recent demand over earlier demand. The forecast will be more responsive to change in the underlying average of the demand series. C. The most frequently used time-series forecasting method is exponential smoothing because of its simplicity and the small amount of data needed to support it. D. In exponential smoothing, higher values place greater weight on earlier demands in computing the average. E. When a significant trend exists, regression method may be effective. O A, B and E O A, D and E O A and D O C, D and E

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
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No need to answer everything! Just plot the actual visitors and the forecasts. Compare the accuracy of the forecasts in the 1985 to 1990 period with those subsequent to that period.
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If actual period demand varies from the forecast by more than 3MAD, this indicates: there is 3% chance that the forecast is wrong. there is a 98% chance that the forecast is wrong. there is a 97% chance that the forecast is wrong. there is a 3% chance that the forecast is correct Moving to the next question prevents changes to this answer:
For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83. a. Compute for a 3 month moving average forecast. b. Compute for the exponential smoothing forecast for a=0.2. c. Which provides the better forecast using MSE as the measure of model accuracy? d. What is the forecast for next month?
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