Project 2: How much does education affect wage rates? The data file cps4_small.dta contains 1000 observations on hourly wage rates, education, and other variables from the 2008 Current Population Survey (CPS). (a) Obtain the summary statistics and histograms for the variables WAGE and EDUC. Discuss the data characteristics, especially appropriate summary statistics (mean, median) and shape of the data. (b) Estimate the linear regression WAGE = B1 + B2EDUC + e and discuss the results. Interpret the regression coefficients and comment on the quality of the fit. (c) Calculate the least squares residuals and plot them against EDUC. Are any patterns evident? Comment on the assumptions (linearity, normality of errors, and constant variance of errors) of classical linear regression model. (d) Estimate the quadratic regression WAGE = a1 + a2EDUC + e and discuss the results. (e) Plot the fitted linear model from part (b) and the fitted values from the quadratic model from part (d) either in the same or separate graph with the data on WAGE and EDUC. Which model appears to fit the data better? Compare the sum of squared residuals (RSS) from the models in (b) and (d). Which model has a lower RSS