Câu hỏi: Which of the following is the most accurate definition of the term “the OLS estimator”?

A. It comprises the numerical values obtained from OLS estimation

B. It is a formula that, when applied to the data, will yield the parameter estimates

C. It is equivalent to the term “the OLS estimate”

D. It is a collection of all of the data used to estimate a linear regression model.

Câu 1: The type I error associated with testing a hypothesis is equal to:

A. One minus the type II error

B. The confidence level

C. The size of the test

D. The size of the sample

Câu 2: What is the relationship, if any, between the normal and t-distributions?

A. A t-distribution with zero degrees of freedom is a normal

B. A t-distribution with one degree of freedom is a normal

C. A t-distribution with infinite degrees of freedom is a normal

D. There is no relationship between the two distributions

Câu 3: What result is proved by the Gauss-Markov theorem?

A. That OLS gives unbiased coefficient estimates

B. That OLS gives minimum variance coefficient estimates

C. That OLS gives minimum variance coefficient estimates only among the class of linear unbiased estimators

D. That OLS ensures that the errors are distributed normally

Câu 4: Which of the following is the correct value for?

A. 2.89

B. 1.30

C. 0.84

D. We cannot determine the value of from the information given in the question

Câu 5: Which one of the following is NOT an assumption of the classical linear regression model?

A. The explanatory variables are uncorrelated with the error terms

B. The disturbance terms have zero mean

C. The dependent variable is not correlated with the disturbance terms

D. The disturbance terms are independent of one another

Câu 6: Consider an increase in the size of the test used to examine a hypothesis from 5% to 10%. Which one of the following would be an implication?

A. The probability of a Type I error is increased

B. The probability of a Type II error is increased

C. The rejection criterion has become more strict

D. The null hypothesis will be rejected less often