Question

In: Statistics and Probability

Conduct a study in a statistics class to measure the effect of solving problems at home...

Conduct a study in a statistics class to measure the effect of solving problems at home on the performance on the final exam. She collected data at random for 10 students from a class on the number of hours spent in a week doing problem sets at home (X) and their score on the final exam (Y), as shown in the following table

X = number of hours per week

Y = score on the final exam

10

80

15

85

24

95

5

80

8

90

4

80

20

95

24

100

30

85

18

70

What are the regression slope and vertical intercept? Write the equation for the line.

Predict the final score of a student who studies for 12 hours every week.

Find the coefficients of determination and non-determination. What do they mean

Perform an F-test for the significance of the regression at 0.05 level of significance. What does it mean

Solutions

Expert Solution

X Y SUMMARY OUTPUT
10 80
15 85 Regression Statistics
24 95 Multiple R 0.876000225
5 80 R Square 0.767376394
8 90 Adjusted R Square 0.728605793
4 80 Standard Error 4.162404636
20 95 Observations 8
24 100
ANOVA
df SS MS F Significance F
Regression 1 342.9213259 342.9213 19.79274 0.004334241
Residual 6 103.9536741 17.32561
Total 7 446.875
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 76.37380192 3.023662612 25.2587 2.54E-07 68.97516604 83.7724378
X 0.854632588 0.192099617 4.448903 0.004334 0.384581759 1.324683417

The regression slope=0.8546 and vertical intercept=76.3738 and the regression equation is:

Predicted final score of a student who studies for 12 hours every week=76.3738+0.8546*12=86.63.

The coefficients of determination=R2=0.7674

The coefficients of non-determination=1-R2=1-0.7674=0.2326.

76.74% of total variation in score on the final exam in the sample is explained by this regression equation and 23.26% of total variation in score on the final exam in the sample is not explained by this regression equation.

From ANOVA table, value of F-test=19.7927 and corresponding P-value=0.0043<0.05 so the regression equation is significant at 0.05 level of significance.


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