BUSN 5000 Final Exam Questions and
Already Passed Answers 2025-2026.
The ______ captures how the population average of one random variable varies with the values
of another random variable. - Answer CEF
If we say E(y|x)=β1+β1x, where β0 and β1 solve the population least-squares problem, then the
CEF is the population regression _____ and β0 and β1 are population regression _____. -
Answer function, coefficients
The population regression function provides the best ______ to the CEF. - Answer linear
approximation
The population regression function provides the best _____ of the dependent variable, given
the explanatory variables - Answer linear predictor
The coefficient β1 measures the _____ in y _____ with a _____ in x1, holding all of the
unobservables constant. - Answer change, associated, unit change
If β0 and β1 solve the population least-squares problem their values ______ the expected value
of the _____ difference between the dependent variable and the CEF. - Answer minimize,
squared
The value of β1 that solves the population least-squares problem is: - Answer
β1=cov(xi1yi)E(x2i1)
The OLS estimator for β1 can be obtained by plugging in the _____ of xi and yi for their ______
and plugging in another _____ for each outer expectation. - Answer sample averages,
population average, sample average
If there were more than one x in (1), then the formula for β1 would be the _____, except xi1
would be replaced with the _____ from a regression of xi1 on the other xs. - Answer same,
residual
The ______ theorem says you can control for other explanatory variables in estimating the
, If E(ui|xi1)=0 in (1), xi1 is _____ of ui and the sampling error of β̂ 1 equals ______ on average,
which implies that β̂ 1 is ______. - Answer mean independent, 0, unbiased
If E(ui|xi1)=0 in (1), the sampling error of β̂ 1converges to _____ and β̂ 1 is ______. - Answer
0, consistent
If you omit xi2 from (2), β̂ 1 will be unbiased only if β2= ______ or xi1 and xi2 are ______. -
Answer 0, uncorrelated
If you omit xi2 from (2), β̂ 1 will be biased ______ if β2 and cov(xi1,xi2) have the same ______. -
Answer upward, sign
If xi1 is education and xi2 is labor market experience, and you omit xi2 from (2), then β̂ 1 will be
biased ______ because β2 is _____ and cov(xi1,xi2) are _____ correlated. - Answer downward,
positive, negatively
Let's say you don't omit xi2, but it is measured with error. Then β̂ 2 will be ______ . (unbiased/
biased down/ biased up) - Answer biased down
R2 measures how much of the variance of the ______ variable is accounted for by the ______
variables. - Answer dependent, explanatory
True or false: R2 is centrally important for doing causal inference - Answer fasle
Basic OLS inference is grounded in the application of the _____, which says that the ______ of
the OLS estimator can be regarded as approximately _____ for large samples. - Answer CLT,
sampling distribution, normal
The modern approach to regression inference is to allow for the variance of the regression
errors to allow for _____, which implies the variance of the errors depends on the ______. -
Answer heteroscedasticity, explanatory variables
The modern approach means we should always report _____ standard errors and test statistics.
- Answer robust
Already Passed Answers 2025-2026.
The ______ captures how the population average of one random variable varies with the values
of another random variable. - Answer CEF
If we say E(y|x)=β1+β1x, where β0 and β1 solve the population least-squares problem, then the
CEF is the population regression _____ and β0 and β1 are population regression _____. -
Answer function, coefficients
The population regression function provides the best ______ to the CEF. - Answer linear
approximation
The population regression function provides the best _____ of the dependent variable, given
the explanatory variables - Answer linear predictor
The coefficient β1 measures the _____ in y _____ with a _____ in x1, holding all of the
unobservables constant. - Answer change, associated, unit change
If β0 and β1 solve the population least-squares problem their values ______ the expected value
of the _____ difference between the dependent variable and the CEF. - Answer minimize,
squared
The value of β1 that solves the population least-squares problem is: - Answer
β1=cov(xi1yi)E(x2i1)
The OLS estimator for β1 can be obtained by plugging in the _____ of xi and yi for their ______
and plugging in another _____ for each outer expectation. - Answer sample averages,
population average, sample average
If there were more than one x in (1), then the formula for β1 would be the _____, except xi1
would be replaced with the _____ from a regression of xi1 on the other xs. - Answer same,
residual
The ______ theorem says you can control for other explanatory variables in estimating the
, If E(ui|xi1)=0 in (1), xi1 is _____ of ui and the sampling error of β̂ 1 equals ______ on average,
which implies that β̂ 1 is ______. - Answer mean independent, 0, unbiased
If E(ui|xi1)=0 in (1), the sampling error of β̂ 1converges to _____ and β̂ 1 is ______. - Answer
0, consistent
If you omit xi2 from (2), β̂ 1 will be unbiased only if β2= ______ or xi1 and xi2 are ______. -
Answer 0, uncorrelated
If you omit xi2 from (2), β̂ 1 will be biased ______ if β2 and cov(xi1,xi2) have the same ______. -
Answer upward, sign
If xi1 is education and xi2 is labor market experience, and you omit xi2 from (2), then β̂ 1 will be
biased ______ because β2 is _____ and cov(xi1,xi2) are _____ correlated. - Answer downward,
positive, negatively
Let's say you don't omit xi2, but it is measured with error. Then β̂ 2 will be ______ . (unbiased/
biased down/ biased up) - Answer biased down
R2 measures how much of the variance of the ______ variable is accounted for by the ______
variables. - Answer dependent, explanatory
True or false: R2 is centrally important for doing causal inference - Answer fasle
Basic OLS inference is grounded in the application of the _____, which says that the ______ of
the OLS estimator can be regarded as approximately _____ for large samples. - Answer CLT,
sampling distribution, normal
The modern approach to regression inference is to allow for the variance of the regression
errors to allow for _____, which implies the variance of the errors depends on the ______. -
Answer heteroscedasticity, explanatory variables
The modern approach means we should always report _____ standard errors and test statistics.
- Answer robust
