Câu hỏi: 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 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: 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 3:  Which of the following is NOT a good reason for including lagged variables in a regression?

A. Slow response of the dependent variable to changes in the independent variables

B. Over-reactions of the dependent variables

C. The dependent variable is a centred moving average of the past 4 values of the series

D. The residuals of the model appear to be non-normal

Câu 4: 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 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: 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