1. Given the data in the table below, evaluate each of the forecasting methods listed in parts a through d below. To do so, use the data to compute the forecast that would have been computed for each month of years 2 through 5. Then use these forecasts to compute the bias, MSE and MAD. Which of the four methods do you prefer and why? For each method, what is the forecast demand for January of Year 6? Plot the demand data and the forecast errors and describe the overall patterns that you see. Hint: For the exponential smoothing forecasts, you need an initial forecast. Use the average of the first twelve months of demand data (i.e., the average monthly demand for year 1) as the initial forecast

2. Sales	Year1	YEar2	Year 3	Year4	Year 5
   JAn	1103	1095	1013	1122	1063
   Feb	1113	1256	932	949	882
   march	968	872	1076	902	1237
   April	721	1254	1239	1217	1137
   may	753	943	781	1262	811
   june	1026	1020	1214	1084	1103
   july	968	1249	954	1130	1089
   aug	1109	1247	891	792	1065
   sept	1041	1244	923	1006	719
   oct	957	799	840	1076	853
   nov	803	723	785	738	1174
   dec	1005	763	1161	1176	1114
   total	11567	12465	11809	12454	12247

3. find

4. 1) A moving average with N= 10

5. 2) A moving average with N = 3

6. 3) Exponential smoothing with a = 0.2

7. 4) Exponential smoothing with a = 0.6