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1.Multiple linear regression analysis determines the
a. true value of the population slope
b. linear relationship between the dependent variable and exactly one independent variable.
c. linear relationship between the dependent variable and many independent variables.
d. true value of the population intercept.
2.Suppose you wish to explain student midterm scores by time taken to complete the exam and you are concerned that the marginal effect of time taken differs depending on the amount of time taken in a quadratic manner. You could control for this possibility by estimating the population regression function
a. Midterm Score = β0 + β1 ∙ Time Taken + ε.
b. Midterm Score = β0 + β1 ∙ Time Taken2 + ε.
c. Midterm Score = β0 + β1 ∙ Time Taken + β2 ∙ Time Taken2 + ε.
d. Midterm Score = β0 + β1 ∙ Time Taken + β2 ∙ Time Taken2 + β3 ∙ Time Taken3 + ε.
3.Outliers are potentially problematic because they
a.result in biased estimates.
b.skew the data to the right.
c.skew the data to the left.
d.result in larger estimated standard errors.
4.One can deal with potential outliers by
a.dropping them from the data set.
b.including a dummy variable equal to 1 if the observation is an outlier.
c.performing Weighted Least Squares.
d.dividing the value of outlier by the sample mean.
5.Suppose you are estimating salary as a function of age, education, hours of work and the number of young children and you are concerned that the salary functions differ for men and women. You could test this possibility by performing a
a. t-test for individual significance
b.t-test for joint significance
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