Multiple Linear Regression Question

Question

The computer output shown below is part of the regression analysis to predict the height of the gold medal winning high jump in the Olympics based on year and gender.

 

Predictor        Coef               SECoef          T              P
Constant       -9.0965            0.4708       -19.32       0.000
Year              0.0057426      0.0002409    23.84       0.000
Gender(M=0)  -0.34761         0.01537                     0.000

Source          Df           SS            MS         F         P
Regression     2          2.0735     1.0368              0.000
Error             4          0.1015      0.0024
Total            44          2.1751

 

The model has

A. One Quantitative predictor and one categorical predictor

B. One quantitative predictor, one categorical predictor, and interaction

C. Two quantitative predictors

D. Two quantitative predictors and interaction

E. Two categorical predictors and interaction

Answer 1

Gender is a categorical predictor (0 or 1), although when written as a number, it could potentially allow numbers between 0 and 1. But I would still consider it categorical.

Year is quantitative, since you would enter the number of the year (2000, 2004, 2024, etc).

There are no interactions included in this model.

Therefore, answer A seems correct.