The following regression model aims to test whether a profes

The following regression model aims to test whether a professor’s beauty score (bty_avg) and age are associated with the ratings of the professor’s teaching evaluation: rating = Beta0 + Beta1 * age + Beta2 * bty_avg + error_term. The output of the OLS estimation is shown below: coefficents:

                  Estimate std.error          t value          Pr(>ItI)

(intercept)    4.054732            0.169865         23.870          <2e-16

age    -0.003059 0.002664        -1.148           0.251396

bty_avg       0.060656             0.017098          3.548          0.000429

(1) The model’s estimates for Beta1 and Beta2 are: Beta1 = ____________, Beta2 = __________ (2) Indicate the estimate(s) that is/are different from 0 with substantial statistical significance (p-value<0.1): __ Beta1 __Beta2 (3) On average, one unit increase of a professor’s beauty score (bty_avg) is associated with ____ units [Increase | Decrease] (choose one) in the professor’s rating.

Solution

(1) The model’s estimates for Beta1 and Beta2 are: Beta1 = -0.003059 , Beta2 = 0.060656 ....

(2) Beta2..
p-value = 0.000429 < 0.1 ..so it is different from 0 with substantial statistical significance ...

3) On average, one unit increase of a professor’s beauty score (bty_avg) is associated with 0.060656 units Increase in the professor’s rating...