ANOVA df SS MS F Significance F Regression 1 335.0472 335.0473 178.3859 Residual 1.8782 Total 50 427.0798 Coefficients Standard t Stat P-value Lower Upper Error 95% 95% Intercept -1.8940 0.4018 -4.7134 2.051E- -2.7015 -1.0865 05 Hours 0.9795 0.0733 13.3561 5.944E- 0.8321 1.1269 18 Use this data to answer the following three questions.Questions 23 - 25 are based on the following information. 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 from regressing starting salary on number of hours spent studying per day for a sample of 51 students. NOTE: Some of the numbers in the output are deliberately removed. Regression Statistics Multiple R 0.8857 R Square 0.7845 Adjusted R Square 0.7801 Standard Error 1.3704 Observations 51Referring to the regression output above, the estimated average change in salary per month (in thousands of dollars) as a result of spending an extra hour per day studying is Question 25 1 pts Referring to the regression output above, the 90% confidence interval for the average change in salary per month (in thousands of dollars) as a result of spending an extra hour per day studying is O Wider than [-2.7015, -1.0865] O Wider than [0.8321, 1.1269] O Narrower than [0.8321, 1.1269] O Narrower than [-2.7015, -1.0865] No new data to save. Last checked at 14:17 Submit aring your screen. Stop sharing Hide lacBook ProQuestion 23 1 pts Referring to the regression output above, the error sum of squares (SSE) is Question 24 1 pts Referring to the regression output above, the estimated average change in salary per month (in thousands of dollars) as a result of spending an extra hour per day studying is