(a) (b) Week 1 2 3 4 5 6 Value | 18 | 11 | 15 0116 | 13 Construct a time series plot. 20 20 20 20 18 18 18 18 E 16 E 16 E 16 E 16 = 14 = 14 g 14 = 14 w 12 w 12 w 12 w 12 10 = 10 > 10 v 8 w8 w8 w8 g o g o o g o g a 4 F o4 o4 2 2 2 2 0 + + o o o 1 2 3 4 3 3 4 3 4 3 4 5 Week Week @0 Week 0 Week What type of pattern exists in the data? ) The data appear to follow a seasonal pattern. () The data appear to follow a horizontal pattern. The data appear to follow a cyclical pattern. ) The data appear to follow a trend pattern. Develop the three-week moving average forecasts for this time series. (Round your answers to two decimal places.) Week 1im\\fa|5:;ies Forecast 1 18 2 11 3 15 4 10 5 16 6 13 MSE = 13 What is the forecast for week 77 Compute MSE. (Round your answer to two decimal places.) (c) Use a = 0.2 to compute the exponential smoothing forecasts for the time series. Week Time Series Value Forecast 18 2 11 3 15 4 10 5 16 6 13 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (Round your answer to two decimal places.) (d) Compare the three-week moving average approach with the exponential smoothing approach using a = 0.2. Which appears to provide more accurate forecasts based on MSE? Explain. O The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach. The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach. The exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach. O The exponential smoothing using a = 0.2 provides a better forecast since it has a smaller MSE than the three-week moving average approach. (e) Use a smoothing constant of a = 0.4 to compute the exponential smoothing forecasts. Week Time Series Value Forecast 1 18 2 11 3 15 4 10 5 16 6 13 Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. The exponential smoothing using a = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.4. O The exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.4