The following regression results were obtained for various models, with the dependent variable in each model being POV: Models of Poverty Rate Variable Constant FAM HS UNEM URB SOUTH GDP DEM R Model A A. B. 27.99 (5.66) -2.42 (1.22) -3.52 (1.18) 12.33 (4.86) 1.33 (1.10) 13.51 (5.67) -0.12 (0.05) -1.80 (0.96) 0.7286 Model B 27.81 (5.21) -3.91 (1.58) -2.99 (1.05) 1.67 (1.50) 11.61 (4.99) 0.02 (0.05) 0.6732 Model C 26.71 (6.62) 2.79 (1.80) 12.41 (5.77) -1.99 (0.90) 0.5832 Note: The estimated coefficients are reported in the table with their corresponding standard errors given in parentheses below each coefficient. Empty spaces correspond to variables not included in the model. Solely based on adjusted R-squared, which model above is most preferred? With respect to Model A, suppose you believe that each of the estimated coefficients individually influences the poverty rate in the population (i.e., each respective coefficient in the population model differs from zero). Using a 5% level of significance, test appropriate hypotheses consistent with your beliefs and discuss the results of your tests. C. With respect to Model B, suppose you believe that the coefficient of FAM in the population model differs from - 1. Provide the null and alternative hypotheses below. Based on the estimated results above, at the 1% level of significance, what do you decide with respect to your hypotheses? Explain your results. D. With respect to Model C, at the 10% level of significance, test whether or not the slope coefficients are jointly equal to zero in the population model (That is, do they all equal zero?). Make sure to provide all necessary information.