Consider the following time series data. Week 1 2 3 4 5 6 Value 17 12 15 10 16 13 (a) Construct a time series plot. 20 18 20 18 16 14 Time Series Value iniwlwm 20 18 16 14 12 10 8 20 18 16 14 12 10 8 6 4 2 0 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 Week Week Week Week What type of pattern exists in the data? O The data appear to follow a trend pattern. The data appear to follow a seasonal pattern. The data appear to follow a cyclical pattern. The data appear to follow a horizontal pattern. (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 1 17 2 12 3 15 4 10 16.62 5 16 16.99 6 13 17.36 Compute MSE. (Round your answer to two decimal places.) What is the forecast for week 7? 17.73 (c) Use a = 0.2 to compute the exponential smoothing values for the time series. Week Time Series Value Forecast 1 17 2 2 12 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 forecast with the exponential smoothing forecast using a = 0.2. Which appears to provide the better forecast based on MSE? Explain. The exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach. 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 smaller MSE than the three-week moving average approach. (e) Use a = 0.4 to compute the exponential smoothing values for the time series. Week Time Series Value Forecast 1 17 2 12 3 15 4 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. The exponential smoothing using a = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.2. The exponential smoothing using a = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.2. 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