Question 3 (Forecasting) - Consider the following time series data. Week 1 2 3 4 5 6. Value 18 13 16 11 17 14 a. Construct a time series plot. What type of pattern exists in the data? b. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 7 c. Use a = .2 to compute the exponential smoothing forecasts for the time series. Compute MSE and a forecast for week 7 d. Compare the three-week moving average approach with the exponential smoothing approach using a = .2. Which appears to provide more accurate forecasts based on MSE? Explain. e. Use a smoothing constant of a = .4 to compute the exponential smoothing forecasts. Does a smoothing constant of .2 or .4 appear to provide more accurate forecasts based on MSE? Explain.
Question 3 (Forecasting) - Consider the following time series data. Week 1 2 3 4 5 6. Value 18 13 16 11 17 14 a. Construct a time series plot. What type of pattern exists in the data? b. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 7 c. Use a = .2 to compute the exponential smoothing forecasts for the time series. Compute MSE and a forecast for week 7 d. Compare the three-week moving average approach with the exponential smoothing approach using a = .2. Which appears to provide more accurate forecasts based on MSE? Explain. e. Use a smoothing constant of a = .4 to compute the exponential smoothing forecasts. Does a smoothing constant of .2 or .4 appear to provide more accurate forecasts based on MSE? Explain.
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter13: Regression And Forecasting Models
Section: Chapter Questions
Problem 42P: The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars)...
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