The past 18 weekly sales (y,) for a product are given in the following table. Week...

 

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The past 18 weekly sales (y,) for a product are given in the following table. Week Sales Week Sales 1 98 10 170 200 190 220 210 2345 6 7 8 9 100 110 150 140 160 200 150 156 12 13 14 15 16 17 18 260 258 270 240 Assume that the model applicable to these data is given by the equation y, = Bo + B₁t+ €, where t indicates time (here week) with t = 1, 2, . . ., 18. (1.1) Use the method of least squares to estimate and ₁, then write down the fitted model. [8] (1.2) Calculate the point forecast and the 95% prediction interval for product sale in week 19. [10] (1.3) Calculate the coefficient of determination R² and the adjusted coefficient of determination [10] [12] Radi (1.4) Test for positive autocorrelation by using the Durbin-Watson statistic with a = 0.05. The past 18 weekly sales (y,) for a product are given in the following table. Week Sales Week Sales 1 98 10 170 200 190 220 210 2345 6 7 8 9 100 110 150 140 160 200 150 156 12 13 14 15 16 17 18 260 258 270 240 Assume that the model applicable to these data is given by the equation y, = Bo + B₁t+ €, where t indicates time (here week) with t = 1, 2, . . ., 18. (1.1) Use the method of least squares to estimate and ₁, then write down the fitted model. [8] (1.2) Calculate the point forecast and the 95% prediction interval for product sale in week 19. [10] (1.3) Calculate the coefficient of determination R² and the adjusted coefficient of determination [10] [12] Radi (1.4) Test for positive autocorrelation by using the Durbin-Watson statistic with a = 0.05.