Exhibit 4 shows the multiple linear regression with (alpha) = 0.05, for the perc
ID: 3320608 • Letter: E
Question
Exhibit 4 shows the multiple linear regression with (alpha) = 0.05, for the percentage of high school graduates who attend four-year college (college attendance rate).
Please answer Question 36-40.
37. How many percent of college attendance rate’s variation can be determined by the independent variables in this regression?
38%
60%
30%
6.2%
38. For some reason, the standard error for the average class size is missing. The value of the standard error should be
A. unavailable unless using MS Excel calculation.
2.056.
1.007
0.993.
39. Can you confirm the estimated equation’s overall significance by F-test?
No, because the p-value
of Average Class Size is greater than 0.05.
Yes, because the p-value
of F test is less than 0.05.
Yes, because the test statistic is negative.
No, because the p-value
of F test is greater than 0.025.
40. Which of the following modifications is least likely to raise R-square in this case?
Choose another data set for a higher R square and consistent testing results.
Drop the independent variable of average class size.
Keep all variables and change the model to be exponential (log-linear) model. .
D. Add another independent variable such as student family income.
Class Size (# of students) -1.4297536 ? -1.43972625 0.17048811 Combined
SAT Score 0.07573703 0.039055144 1.93923323 0.07151948
Explanation / Answer
37) percent of college attendance rate’s variation can be determined by the independent variables in this regression
=r2 =0.3821 =38% option A is correct
38) value of the standard error should be =coefficient/t stat =-1.4297536/-1.43972625 =0.993
option D
39) option B is correct
40)
Drop the independent variable of average class size.
B.Drop the independent variable of average class size.
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