Consider the following time series data. Week 1 2 3 4 5 6 Value 19 14 16 12 17 15 A. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 7 (to 2 decimals if necessary). MSE ______ The forecast for week 7 _______ B. Use a = 0.2 to compute the exponential smoothing forecasts for the time series. Compute MSE and a forecast for week (to 2 decimals). MSE _____ The forecast for week 7 ____ C. Use a smoothing constant of a = 0.4 to compute the exponential smoothing forecasts. Compute MSE (to 2 decimals)

Consider the following time series data. Week 1 2 3 4 5 6 Value 19 14 16 12 17 15 A. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 7 (to 2 decimals if necessary). MSE __ The forecast for week 7 _ B. Use a = 0.2 to compute the exponential smoothing forecasts for the time series. Compute MSE and a forecast for week (to 2 decimals). MSE _ The forecast for week 7 __ C. Use a smoothing constant of a = 0.4 to compute the exponential smoothing forecasts. Compute MSE (to 2 decimals)

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.7: Exponential Smoothing Models

Problem 27P: The file P13_27.xlsx contains yearly data on the proportion of Americans under the age of 18 living...

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The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.
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