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

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30/08/2021
3.6 8 Đánh giá

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.

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Câu hỏi khác cùng đề thi
Câu 1: What is the relationship, if any, between t-distributed and F-distributed random variables?

A. A t-variate with z degrees of freedom is also an F(1, z)

B. The square of a t-variate with z degrees of freedom is also an F(1, z)

C. A t-variate with z degrees of freedom is also an F(z, 1)

D. There is no relationship between the two distributions

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30/08/2021 8 Lượt xem

Câu 2: 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

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Câu 3: 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

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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

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30/08/2021 8 Lượt xem

Câu 6: Which of the following is a correct interpretation of a “95% confidence interval” for a regression parameter?

A. We are 95% sure that the interval contains the true value of the parameter

B. We are 95% sure that our estimate of the coefficient is correct

C. We are 95% sure that the interval contains our estimate of the coefficient

D. In repeated samples, we would derive the same estimate for the coefficient 95% of the time

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