
Multiple Regression Analysis Quiz
Authored by Sardor A'zam
Business
University
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15 questions
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1.
MULTIPLE CHOICE QUESTION
20 sec • 1 pt
The multiple regression model does not allow us to examine the effects of individual independent variables on the dependent variable.
True
False
2.
MULTIPLE CHOICE QUESTION
20 sec • 1 pt
When we use OLS method, both parameters and variables need to be linear, otherwise we cannot use OLS method.
True
False
3.
MULTIPLE CHOICE QUESTION
20 sec • 1 pt
The method of OLS can be applied to estimate the multiple regression model.
True
False
4.
MULTIPLE CHOICE QUESTION
20 sec • 1 pt
R-squared is the proportion of the sample variation in the dependent variable explained by the independent variables, and it serves as a goodness-of-fit measure.
True
False
5.
MULTIPLE CHOICE QUESTION
20 sec • 1 pt
It is important to put too much weight on the value of R-squared when evaluating econometric models.
True
False
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Under the first four Gauss-Markov assumptions (MLR.1 through MLR.4), the OLS estimators are unbiased. This implies that including an irrelevant variable in a model has no effect on the unbiasedness of the intercept and other slope estimators. On the other hand, omitting a relevant variable causes OLS to be biased.
False
True
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
We use t statistics to test hypotheses about a single parameter against one- or two-sided alternatives, using one- or two-tailed tests, respectively. The most common null hypothesis is H0: bj = 0, but we sometimes want to test other values of bj under H0.
False
True
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