Consider the partial printout for an interaction regression analysis of the relationship between a dependent variable y and two independent variables x1 and x2. ANOVA Regression Residual Total df369 SS 3393.6773240.7226759873394.4 MS 1131.2257750.120445998F9391.974782 Significance F2.11084E−11 Intercept X1 X2 X1X2 Coefficients 16.72197014−3.037317759−1.0465227544.071685147 Standard Error 8.2839972192.6787487051.5471326450.444059933t Stat 2.018587126−1.133856921−0.6764272979.169224345 P-value 0.090076540.3001163820.5239739889.47663E−05 Lower 95% −3.548255659−9.591984506−4.8322227272.98510884 Upper 95% 36.992195933.5173489872.739177225.158261454 a. Write the prediction equation for the interaction model.
b. Test the overall utility of the interaction model using the global F -test at α=.05 .
c. Test the hypothesis (at α=.05 ) that x1 and x2 interact positively.
d. Estimate the change in y for each additional 1-unit increase in x1 when x2=6 . 3 Test for Interaction Between Two Variables
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