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Posted: **Wed May 11, 2022 9:03 am**

: Consider The Multiple Regression Output Shown The Regression Equation Is Y 42 6 6 96x1 1 63x2 1 64x3 0 438x4 P 1 (18.02 KiB) Viewed 33 times

: Consider The Multiple Regression Output Shown The Regression Equation Is Y 42 6 6 96x1 1 63x2 1 64x3 0 438x4 P 2 (19.58 KiB) Viewed 33 times

Consider the multiple regression output shown: The regression equation is Y = 42.6 -6.96X1 + 1.63X2 + 1.64X3 + 0.438X4 Predictor Coef SE CoefT P Constant 42.60 18.44 231 0.060 X1 -6.964 1.081 -6.44 0.001 X2 1.629 1.139 1.43 0.202 X3 1.6353 0.5778 283 0.030 X4 0.4375 0.1453 3.01 0.024 S = 204939 R - S - 99.8% R - Sq(adj) - 99.6% Analysis of Variance Source DF SS MS F

Source DF SS MS FP Regression 4 10942.4 2735.6 650.66 0.000 Residual Error 6 25.2 4.2 Total 10 10967.6 What is the coefficient of X2 in the model? What is the p-value for testing this coefficient? Round your answers to three decimal places. Coefficient i p-value: e Textbook and Media