Consider a simple linear regression model to predict hourly wage (USD) based on years of work experience. The partial STATA output below was generated using a sample of 50 women surveyed in 1988. The graph below shows a histogram of the residuals. . regress wage experience wage Coef. Std. Err. t P> t [95% Conf. Interval ] ---+-- experience . 3480623 . 1183965 2.94 0 . 005 . 11001 . 5861145 cons 4.179087 1. 785613 2.34 0 . 023 . 5888717 7.769303Density 8 - O 0 10 Residuals (a) [2 pts] What is the interpretation of the coefficient estimate 0.3480623? (b) [4 pts] Recall assumption #4 of simple linear regression model: E_i ~ N(0, o^2). Using the histogram above, what is the approximate value of s_e (Root MSE) for the regression? Briefly explain your reasoning in 4-6 sentences. (c) [2 pts] Using your approximation for s_e form part (a) and the regression output given above, derive an approximate value of the standard deviation of work experience in the sample. Time left Hide