Question: 1. All the coefficients of the dummy variables in Jame's regression are negative except that for Nov. Does this make sense? Explain. 2. Are you

1. All the coefficients of the dummy variables in Jame's regression are negative except that for Nov. Does this make sense? Explain.
2. Are you happy with Jame's regression model? What changes would you make, if any?
3. Using Jame's fitted model in Table 8-23, generate forecasts for the remaining seven months of 2003.

4. Fit an autoregressive model to Jame's data with sales lagged 12 months as the predictor variable. Is this model reasonable? Generate forecasts for the remaining seven months of 2003 using your autoregressive model.
5. Which model, the dummy variable regression orthe autoregression, do you prefer? Why?
Jame Luna's efforts to understand the trend and seasonality in Surtido Cookies monthly sales have been examined in Cases 3-5, 4-8, and 5-7. The fact that cookie sales are seasonal is now well established. Jame and his team have tried a smoothing procedure, decomposition, and now are interested in trying regression methods in their continuing attempt to come up with a procedure that produces the "best" forecasts of future sales.

TABLE 8-23 Minitab Output for Jame Luna's Regression Model for Surtido Cookie Sales Regression Analysis: SurtidoSales versus Time, Jan, The regression equation is Surtidosales 1703762 4759 Time 1015200 Jan 1259183 Feb 1286031 Mar 1126296 Apr 1188322 May 1170518 Jun - 1108576 Jul-1176156 Aug-355847 Sep-178199 Oct+ 225028 Nov Predictor Constant Time Jan Feb Mar Apr May Coef SE Coet 1703762 107455 2172 124780 15.86 2.19 8.14.000 . 0.000 0.037 4759 -1015200 1.0 2259183 24610-10.11 0.000 2.1 1286031 1244 -10.33 .000 2.1 -1126296 1243839.06 D000 .1 -9.56 0,000 21 -1170518 33527 8.77 0.000 .9 -1108576 133332-8.31 0.000 1.9 -8.83 0 000 1.9 355847 1330492.67 .012 19 -1.34 0.191 1.9 1.69 0.102 19 -1188322 124326 ua Tul Aug Sep oct Nov 1176156 133173 178199 232960 225028 132907 S= 162756 R-Sq= 93.8% R-Sq(adj)= 91.1% Analysis of Variance Source RegresBion Residual Error Total DF 12 1.11783E 13 9.31528E+11 35.1 0.000 28 7.41703E +11 26489395582 40 1.19200E +13 MS Durbin-Watson statistic#1.50

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