1. Imagine we are interested in the relationship between an outcome y1(profit margin of savings and loan companies in a given year) and two predictors, x1 (net revenues in that year) and x2 (number of savings and loan branches offices).

Using the information available, please complete the ANOVA table below.

Coefficients Unstandardized Standardized Coefficients Coefficients 95% Confidence Interval for B Collinearity Statistics Model B Std. Error Beta t Sig Lower Bound Upper Bound Tolerance VIF (Constant) 1.5645 .0794 19.7050 0000 1.3998 1.7292 Net Revenues .2372 0556 9872 4.2693 0003 .1220 .3524 1145 8.7321 Number of Branches -.0002491 0000 -1.7971 -7.7719 0000 -.0003155 -.0001826 1145 8.7321 a. Dependent Variable: Profit MarginModel Df Sum of Mean Square F Sig. Squares Regression A C .2008 E <.001 residual b .0625 d total .4640 a. predictors: number of branches net revenues b. dependent variable: profit margin>