Question: (a) Construct a time series plot. What type of pattern exists in the data? The data appear to follow a trend pattern. The data appear

 (a) Construct a time series plot. What type of pattern existsin the data? The data appear to follow a trend pattern. Thedata appear to follow a seasonal pattern. The data appear to followa cyclical pattern. The data appear to follow a horizontal pattern. D)

(a) Construct a time series plot. What type of pattern exists in the data? 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. D) Develop the three-week moving average for this time series. (Round your answe Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7 ? Use =0.2 to compute the exponential smoothing values for the time series. c) Use =0.2 to compute the exponential smoothing values for the time series. Compute MSE. (Round your answer to two decimal places.) MSE= What is the forecast for week 77 (Round your answer to two decimal places.) d) Compare the three-week moving average forecast with the exponential smoothing forecast using =0.2. Which appears to provide the better forecast based on MSE? Explain. The exponential smoothing using =0.2 provides a better forecast since it has a smaller MSE than the three-week moving average approach. 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 three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach. e) Use =0.4 to compute the exponential smoothing values for the time series. 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 a=0.2. Which appears to provide the better forecast based on MSE? Explain. The exponential smoothing using =0.2 provides a better forecast since it has a smaller MSE than the three-week moving average approach. 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 three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach. (e) Use =0.4 to compute the exponential smoothing values for the time series. Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. The exponential smoothing using =0.2 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 smaller MSE than the exponential smoothing using =0.2. The exponential smoothing using =0.4 provides a better forecast since it has a larger 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

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