Question

A multiple least squares regression was carried out using a sample of 27 observations. From the sample data, the following partial outputs were obtained: SST = ?(yi - ?)² = 288.69, SSE = ?ei² = ?(yi - ?)² = 155.86, Coefficients Predictor Coef SE Coef T Constant 13.187 10.871 1.213 x1 9.37 5.177 1.810 x2 -9.005 3.653 -2.465 x3 -3.286 1.698 -1.935 x4 17.449 12.718 1.372 Answer the following: a) The 96% confidence interval for ?1 is: ( , ) b) One of the data points had x1 = 3.75, x2 = 5.1, x3 = 3.45, x4 = 3.25, and y = 47.32155. Find the predicted value and the residual corresponding to this observation. The predicted value ? = The residual :

          A multiple least squares regression was carried out using a sample of 27 observations. From the sample data, the following partial outputs were obtained: SST = ?(yi - ?)² = 288.69, SSE = ?ei² = ?(yi - ?)² = 155.86, Coefficients Predictor Coef SE Coef T Constant 13.187 10.871 1.213 x1 9.37 5.177 1.810 x2 -9.005 3.653 -2.465 x3 -3.286 1.698 -1.935 x4 17.449 12.718 1.372 Answer the following: a) The 96% confidence interval for ?1 is: ( , ) b) One of the data points had x1 = 3.75, x2 = 5.1, x3 = 3.45, x4 = 3.25, and y = 47.32155. Find the predicted value and the residual corresponding to this observation. The predicted value ? = The residual :

A multiple least squares regression was carried out using a sample of 27 observations. From the sample data, the following partial outputs were obtained: SST = ?(yi - ?)² = 288.69, SSE = ?ei² = ?(yi - ?)² = 155.86, Coefficients Predictor Coef SE Coef T Constant 13.187 10.871 1.213 x1 9.37 5.177 1.810 x2 -9.005 3.653 -2.465 x3 -3.286 1.698 -1.935 x4 17.449 12.718 1.372 Answer the following: a) The 96% confidence interval for ?1 is: ( , ) b) One of the data points had x1 = 3.75, x2 = 5.1, x3 = 3.45, x4 = 3.25, and y = 47.32155. Find the predicted value and the residual corresponding to this observation. The predicted value ? = The residual :

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