Câu hỏi: Which of the following is NOT correct with regard to the p-value attached to a test statistic?

A. p-values can only be used for two-sided tests

B. It is the marginal significance level where we would be indifferent between rejecting and not rejecting the null hypothesis

C. It is the exact significance level for the test

D. Given the p-value, we can make inferences without referring to statistical tables

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

Câu 2: Suppose that we wanted to sum the 2007 returns on ten shares to calculate the return on a portfolio over that year. What method of calculating the individual stock returns would enable us to do this?

A. Simple

B. Continuously compounded

C. Neither approach would allow us to do this validly

D. Either approach could be used and they would both give the same portfolio return

Câu 3: 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

Câu 4: Consider a standard normally distributed variable, a t-distributed variable with d degrees of freedom, and an F-distributed variable with (1, d) degrees of freedom. Which of the following statements is FALSE?

A. The standard normal is a special case of the t-distribution, the square of which is a special case of the F-distribution

B. Since the three distributions are related, the 5% critical values from each will be the same

C. Asymptotically, a given test conducted using any of the three distributions will lead to the same conclusion

D. The normal and t- distributions are symmetric about zero while the F- takes only positive values

Câu 5: Which of the following would NOT be a potential remedy for the problem of multicollinearity between regressors?

A. Removing one of the explanatory variables

B. Transforming the data into logarithms

C. Transforming two of the explanatory variables into ratios

D. Collecting higher frequency data on all of the variables

Câu 6: Which of the following would you expect to be a problem associated with adding lagged values of the dependent variable into a regression equation?

A. The assumption that the regressors are non-stochastic is violated

B. A model with many lags may lead to residual non-normality

C. Adding lags may induce multicollinearity with current values of variables

D. The standard errors of the coefficients will fall as a result of adding more explanatory variables