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
Chọn đáp án: A
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?
Which of the following is a correct interpretation of a “95% confidence interval” for a regression parameter?
Which of the following statements is correct concerning the conditions required for OLS to be a usable estimation technique?
Which of the following is the most accurate definition of the term “the OLS estimator”?
What is the relationship, if any, between the normal and t-distributions?
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?
What is the relationship, if any, between t-distributed and F-distributed random variables?
Which of the following would you expect to be a problem associated with adding lagged values of the dependent variable into a regression equation?
The numerical score assigned to the credit rating of a bond is best described as what type of number?
The type I error associated with testing a hypothesis is equal to:
Which of the following is NOT a good reason for including a disturbance term in a regression equation?
Which one of the following is NOT an assumption of the classical linear regression model?
Two researchers have identical models, data, coefficients and standard error estimates. They test the same hypothesis using a two-sided alternative, but researcher 1 uses a 5% size of test while researcher 2 uses a 10% test. Which one of the following statements is correct?