Question

Table 6

It is believed that, the average numbers of hours spent studying per day (HOURS) during undergraduate education should have a positive linear relationship with the starting salary (SALARY, measured in thousands of dollars per month) after graduation. Given below is the Excel output for predicting starting salary (Y) using number of hours spent studying per day (X) for a sample of 51 students. NOTE: Only partial output is shown.

Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.8857 0.7845 0.7801 1.3704 51 ANO VA MS 1335.0472 335.0473 178.3859 df Significance F Regression Residual Total 1.8782 50 427.0798 Standard CoefficientsError P-value \ 0.0000 0.0000 t Stat Lower 95% Intercept Hours 1.8940 0.9795 0.4018 4.7134 0.0733 13.35611 -2.7015 0.8321 Upper 95% 1.0865 1.1269

Note: 2.051E - 05 = 2.051 ∗ 10-05 and 5.944E - 18 = 5.944 ∗ 10-18.

1. Interpret the estimate of B0, the Y intercept of the line.

1. There is no practical interpretation.

2. About 95% of the starting salaries fall within $1,894 of the least squares line.

3. The starting salary is at least $1,894

4. For every 1 hour spent studying per day, we expect the starting salary to decrease $1,894.

B. The estimated change in mean salary (in thousands of $), as a result of spending an extra hour per day studying is.

1. 0.7845

2. -1.8940

3. 335.0473

4. .9795

C. The value of the measured t test statistic to test whether mean salary depends linearly on HOURS is ____.

1. 13.3561

2. -1.8940

3. 0.9795

4. -4.7134

Answer 1

(A) There is no practical interpretation for the intercept

(B) This is given by the slope = 0.9795

(C) t-statistic = 13.3561