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In a particular college math class, students begin the semester taking a pre-tes

ID: 3160605 • Letter: I

Question

In a particular college math class, students begin the semester taking a pre-test (Pre). At the end of the semester, students receive a final class percentage (Final). Both scores are recorded as percentages out of 100. It was desired to know if performance on the pre-test was predictive of final class percentage. There were 9 students in the class. The results are below: For all of the parts below (except for graphs), please perform the calculations by hand, and show your work. You may use R to check your answers. Make a scatterplot of the data. Does it seem like a straight line model is reasonable? Assuming a straight-line model, compute estimates of the intercept (beta_0) and slope (beta_1). Create a plot of the residuals vs fitted values and a QQ plot of the residuals. Do the necessary regression assumptions seem met? Perform a test of H_0: beta_1 = 0 vs. H_A: beta_1 notequalto 0, using a t-test at alpha = 0.05. Make a conclusion in the context of the problem. Compute R^2 for this regression. If a student scores 80 on the pre-test, what does the model predict will be their final score? Compute the SE of this estimate assuming it is for a single future value.

Explanation / Answer

students   Pre test   Final
1   83   68
2   81   59
3   70   72
4   79   75
5   69   55
6   61   52
7   88   81
8   72   63
9   86   70

Scatter plot


SUMMARY OUTPUT              
                  
Regression Statistics              
Multiple R   0.71              
R Square   0.50              
Adjusted R Square   0.43              
Standard Error   7.27              
Observations   9.00              
                  
ANOVA                  
    df   SS   MS   F   Significance F
Regression   1.00   366.92   366.92   6.94   0.03
Residual   7.00   369.97   52.85      
Total   8.00   736.89           
                  
    Coefficients   Standard Error   t Stat   P-value  
Intercept   8.60   21.96   0.39   0.71  
X Variable 1   0.75   0.29   2.63   0.03  

Regression Eqn is
Y = 8.6 + 0.75 X1(pre test)
Y at 80 = 8.6 + 0.75 X 80 = 68.6

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