Centervilie Bkes and Stuff (CBS) selis motorcycles and accessorses, The number of heimets sold by CeS per week for the past six weeks follows. (a) Construct a time series plot: D What trpe of pattern exists in the data? The data aspear to follow a cyelical pattem. The data appear to follow a horitomal pattern. The data appear to follow a seasonal pattern. The data appear to follow a trend pattern. (b) Develop the three-week, moving average for this time series. (Found your answers to two decimal places.) Compute MSE. (Round your answer to two decimal places.) NSE = What is the forecast for week n ? Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7 ? (Alound your answer to two decimal placets.) (d) Compare the three-week moving average forecast with the expenential smoothing forecast using a =0.2. Which appears to provide the better forecast based on MSt? Explain. The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach. The exponential smoothing using a=0.2 provides a better forecast since it has a larger MSt than the three-week moving average approach. The three-week moving average peovides a better forecast since in has a smaller MSE than the smocking opproach. The exponential smoothing using a =0.2 provides a better torecast 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. Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on NSE? Explain. The exponentiat 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 if has a smaller Mst than the exponential smoothing using =0.2. The exponential smooking using a=0.2 provides a better forecast since it has a targer Mse than the exponential smoothing using a=0.4, The exponential smoching ussing a=0,2 provides a better forecast since it has a smalier MsE than the exponential smoothing using a=0.4