Consider the following time series data. Time Series Value Week 1 Time Series Value (a) Construct a time series plot. 20 18 6420856420 16 14 12 10 0 Value 19 12 14 11 15 13. 20 18. 16 14 12 10 8 2 6 1 3 2 4 3 4 5 Week 6 DE @O Time Series Value DEKHNORSINO 20 18 16- 14 12 10 8 6 4 2 0- 20 18 16 14 12 10 0 8- H 2 3 4 Week 15 6 G What type of pattern exists in the data? O The data appear to follow a trend pattern. O The data appear to follow a seasonal pattern. O The data appear to follow a cyclical pattern. O The data appear to follow a horizontal pattern. (b) Develop the three-week moving average for this time series. Time Series Value Week 1 2 3 4 5 6 19 12 14 11 15 13 Forecast Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (c) Use a 0.2 to compute the exponential smoothing values for the time series. Week Time Series Value 1 2 n 4 5 6 19 12 14 11 13 Forecast 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. Time Series Value Week 1 2 3 4 in 5 6 19 12 14 11 15 13 Forecast Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. 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 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. O The exponential smoothing using or 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.2