Gonsder the foulowing time series data. (a) Construct a time senes plot: What type of pattern exivts in the data? The cata appes to foliov a honiontal pattern The eati appear to follow a veasional botem. The data avpear to follow a syctical pattern. The data appear to follow a trend nattern. (b) Develep the three-week moving average forecasts for this time series. ifiound reur atowers to tame decirhal piaceth.) Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7 ? (c) Use =0.2 to compute the exponential smoothing forecasts for the time sories, (Use all decimal bisces as given in Excel). 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 =0.2. Which appears to provide more accurate forecasts based on MSE? Explain. The exponential smoothing using =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 exponential smoothing using =0.2 provides a better forecast since it has a smaller MSE than the threeweek moving average approach. The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach. (e) Use a smoothing constant of a=0.4 to compute the exponential smoothing forecasts. (Use all decimal places as given in Excel). Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. The exponential smoothing using =0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using =0.2. The exponential smoothing using =0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using =0.4. The exponential smoothing using =0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using =0.4. The exponential smoothing using =0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using =0.2