In: Statistics and Probability
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
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.