Exhibit D df 11,064 172.24 0.0000 0.0153 Adj R-squared0.0152 101.32 Source MS Nu

Question

Exhibit D df 11,064 172.24 0.0000 0.0153 Adj R-squared0.0152 101.32 Source MS Number of obs- F (1, 11062) 1768300.97 113569163 1 1768300.97 Prob> F Model Residual 11,062 10266.603 R-squared Total 115337464 11,063 10425.5142 Root MSE coach fare Coef. Std. Err t >It [95% Conf. Interval] -19.777761.506997 -13.12 0.000 269.4003 1.581759 170.32 0.000 -22.73175-16.82378 272.5008 num car dir1 cons 266.2998 12. (2 points) Based on the output, we are regressing (A) on (B). What are (A) and (B)? Explicitly state them. 13. (4 points) Intuitively, does the sign of the estimated slope coefficient make sense? Why or why not? Provide a clear explanation.

Explanation / Answer

12. Here (A): Coach_fare , is response variable.

(B): Mu,_car_dir_cons , is explaintory variable.

13. The value of estimated slope coefficient tells you how much the predicted value changes when the corresponding predictor is increased by 1 unit. If estimated slope coefficient has negative sign , the predicted value decreases otherwise increases

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