PLS ANWER NO EXCEL

a) You are given below the correlation matrix for variables Education, Experience, and Female. Suppose that we are interested in finding the impact of education on earnings. Based on the correlation matrix, should we care about omitted variable bias? If we should, what would be your next action? b) You run the regression of Wage on Education, Experience and Female. Interpret the OLS results for different models. Do OLS results provide further evidence on omitted variable bias? Does it make sense to include Experience and Female to the regression model? c) The standard errors of coefficients are calculated relying on the homoscedasticity assumption. Do you think our model suffer from heteroscedasticity problem? How would you detect the heteroscedasticity? If not, what is your solution for heteroscedasticity problem? a) You are given below the correlation matrix for variables Education, Experience, and Female. Suppose that we are interested in finding the impact of education on earnings. Based on the correlation matrix, should we care about omitted variable bias? If we should, what would be your next action? b) You run the regression of Wage on Education, Experience and Female. Interpret the OLS results for different models. Do OLS results provide further evidence on omitted variable bias? Does it make sense to include Experience and Female to the regression model? c) The standard errors of coefficients are calculated relying on the homoscedasticity assumption. Do you think our model suffer from heteroscedasticity problem? How would you detect the heteroscedasticity? If not, what is your solution for heteroscedasticity