(a) (10 points) Use the moving averages method to forecast the demand in periods 11-30, taking into account the latest demand information. Find the value of N{5,7,9} that minimizes the MAD calculated via the forecast errors in periods 1130. (b) (10 points) Use the exponential smoothing method to forecast the demand in periods 1130, taking into account the latest demand information. Use the demand observations in periods 110 to initialize F11. Find the value of {0.1,0.2,0.3} that minimizes the MAD calculated via the forecast errors in periods 1130. (c) (15 points) Use Holt's method to forecast the demand in periods 11-30, taking into account the latest demand information. Use the demand observations in periods 110 to initialize S10 and G10. Find the values of {0.1,0.2,0.3} and {0.1,0.2} that minimize the MAD calculated via the forecast errors in periods 1130. (d) ( 15 points) For every week t3, using all demand observations in weeks 1 to t1, calculate the seasonal factor as well as the forecast for each day of the week. Also, calculate the MAD via the forecast errors in periods 1130. (e) ( 25 points) Use Winter's method to forecast the demand in periods 1130, taking into account the latest demand information. Use the demand observations in periods 1-10 to initialize S10,G10,c6,c7,c8,c9, and c10. Assume =0.1. Find the values of {0.1,0.2,0.3} and {0.1,0.2} that minimize the MAD calculated via the forecast errors in periods 1130. (f) (15 points) Which of the above methods yields the least MAD? Forecast the total demand in week 7 with the best method and best parameter values you found. (g) (10 points) Deseasonalize the entire series from period 1 to 30 , fit a simple linear regression, and re-seasonalize the series to forecast the total demand in week 7