Based on the given multiple regression output tables below, answer the following questions: Model Summary ModelRR SquareAdjusted R SquareStd. Error of the EstimateDurbin−Watson1.842.710.630109.4301.158 ANOVA ModelSum of SquaresdfMean SquareFSig. Regression321946.823107315.68.960.0027Residual131723.201111974.8Total453670.0014 Coefficients Unstandardized CoefficientsStandardized CoefficientsModelBStd. ErrorBetatSig.1 (Constant)657.053167.463.92.0024X Variable 15.71031.792−.1013.19.0087X Variable 2−0.41690.322−.077−1.29.2222X Variable 3−3.47151.443−7.996−2.41.0349 (a) State the predictors available in this model. (b) Determine the multiple regression model for this analysis.

Question

Based on the given multiple regression output tables below, answer the following questions: Model Summary ModelRR SquareAdjusted R SquareStd. Error of the EstimateDurbin−Watson1.842.710.630109.4301.158 ANOVA ModelSum of SquaresdfMean SquareFSig.   Regression321946.823107315.68.960.0027Residual131723.201111974.8Total453670.0014 Coefficients Unstandardized CoefficientsStandardized CoefficientsModelBStd. ErrorBetatSig.1 (Constant)657.053167.463.92.0024X Variable 15.71031.792−.1013.19.0087X Variable 2−0.41690.322−.077−1.29.2222X Variable 3−3.47151.443−7.996−2.41.0349 (a) State the predictors available in this model. (b) Determine the multiple regression model for this analysis.

Clara Clark · Accepted Answer

Step 1  Multiple Regression Model is a model in which two or more independent variables are used to predict dependent or response variable.  Step 2  a) Predictors of multiple regression model are as follows:   - X Variable 1   - X Variable 2   - X Variable 3

Witionsion · Accepted Answer

b) Multiple regression model for the given analysis is:  y=β0+β1x1+β2x2+… …+βnxn  y=657.053+β1x1+β2x2+… …+βnxn  =657.053+5.7103x1−0.4169x2−3.4715x3

Based on the given multiple regression output tables below, answer the

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