Suppose from Question 2 that the standard error for the parameter estimate for G
ID: 3159274 • Letter: S
Question
Suppose from Question 2 that the standard error for the parameter estimate for GPA is sb1 = 1,500.
Calculate the test statistic for the following hypothesis test:
H0: ?1 = 0
HA: ?1 ? 0
Select one:
a. t = 2.14
b. t = 1.33
c. t = 0.87
d. t = 2.84
If I wanted to determine how well my sample regression function “fit” the actual data, I would
Select one:
a. do a hypotheses tests on each individual coefficient
b. calculate r2
c. do a hypothesis test on GPA
d. minimize the sum of the squared deviations
Figure 1 shows Excel output estimating the following model:
Salary= ?0 + ?1Male + ?2Experience + ?3Over50 + ?4MBA + ?
Where, Salary = a person’s salary in thousands of dollars, Male = 1 if the person is a male (0 otherwise),Experience = number of years experience, Over50 = 1 if the person is over 50 (0 otherwise) and MBA =1 if the person has an MBA (0 otherwise).
Which coefficient(s) is(are) significant at the .05 level?
Select one:
a. All of them
b. Male, Over50 and MBA
c. Over50 and Experience
d. Experience
Refer to Figure 1
Which of the following is the correct interpretation?
Select one:
a. An increase in experience of 1 year, results in an increase in the predicted salary of around $3,000.
b. A $3,000 increase in experience results in a 1 unit increase in salary.
c. Males earn around $2,000 more than Females for every additional year of experience they have.
d. MBAs make less money than non MBAs.
To test whether the regression equation is significant at the .05 level, which of the following contains the correct Null and Alternative Hypotheses.
Select one:
a. H0: ?3 = 0; HA: ?3 ? 0
b. H0: ?2 = 0; HA: ?2 ? 0
c. H0: ?1 = ?2 = ?3 = ?4 = 0; HA: At least one of the coefficients is not zero
d. H0: ?1 = ?2 = ?3 = ?4 = 0; HA: ?1 ? ?2 ? ?3 ? ?4 ? 0
Refer to Figure 1
What percentage of the variation in salaries is explained by the regression equation?
Select one:
a. 91.3%
b. 76.5%
c. 85.6%
d. 42.3%
What is the total variation in salaries?
Select one:
a. 12,771
b. 1,108
c. 11,663
d. 55.41
Ordinary Least Squares (OLS) produces coefficient estimates by
Select one:
a. maximizing SSE
b. minimizing SSE
c. maximizing SST
d. minimizing SSR
Explanation / Answer
Which coefficient(s) is(are) significant at the .05 level?
Experience because the p value is lwoer than 0.05
Which of the following is the correct interpretation?
a. An increase in experience of 1 year, results in an increase in the predicted salary of around $3,000.
To test whether the regression equation is significant at the .05 level, which of the following contains the correct Null and Alternative Hypotheses.
c. H0: 1 = 2 = 3 = 4 = 0; HA: At least one of the coefficients is not zero
What percentage of the variation in salaries is explained by the regression equation?
R^2 =0.913 = 91.3%
What is the total variation in salaries?
SS of regression =
c. 11,663
Ordinary Least Squares (OLS) produces coefficient estimates by
c. maximizing SST