Consider the following time series data. Month 2 3 4 5 6 7 Value 24 13 20 12 19 23 15 Construct a time series plot. What type of pattern exists in the data? Develop the three-week moving average...


Consider the following time series data.<br>Month<br>2<br>3 4 5 6 7<br>Value<br>24 13 20 12 19 23 15<br>Construct a time series plot. What type of pattern exists in the data?<br>Develop the three-week moving average forecasts for this time series. Compute MSE<br>and a forecast for week 8.<br>b. Use a = .2 to compute the exponential smoothing forecasts for the time series. Com-<br>pute MSE and a forecast for week 8.<br>Compare the three-week moving average approach with the exponential smoothing ap-<br>proach using a = .2. Which appears to provide more accurate forecasts based on MSE?<br>d. Use a smoothing constant of a = .4 to compute the exponential smoothing forecasts.<br>Does a smoothing constant of .2 or .4 appear to provide more accurate forecasts based<br>on MSE? Explain.<br>

Extracted text: Consider the following time series data. Month 2 3 4 5 6 7 Value 24 13 20 12 19 23 15 Construct a time series plot. What type of pattern exists in the data? Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 8. b. Use a = .2 to compute the exponential smoothing forecasts for the time series. Com- pute MSE and a forecast for week 8. Compare the three-week moving average approach with the exponential smoothing ap- proach using a = .2. Which appears to provide more accurate forecasts based on MSE? d. 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.

Jun 09, 2022
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