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Researchers run a second model to better characterize the factors driving income at the laboratory. In this model education in years, age in years, and a dummy variable for employment requiring an engineering degree are included. Results are below: Model Summary Adjusted R Std. Error of R Square Square the Estimate -M a. Predictors: {Constant}, FEMALE, EDUCATION, AGE, ENGINEERING E Coefficientsa Unstandardized Standardized Coefficients Coefficients _m (Constant) 28437.256 587.382 FEMALE 2472.307 268.367 EDUCATION 952.256 241.353 AGE 97.923 15.243 ENGINEERING 8567.34 1034.454 c) Interpret in words the coefficient of the FEMALE variable. Is it statistically significant? Is it practically significant? Explain. d) Interpret in words the coefcients on the control variables. Are they statistically signicant? Are they practically significant? Explain. I e) Do you now believe these results are sufficient to publicly accuse the laboratory of income discrimination? Why or why not