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Test Bank for Introduction to Econometrics 4th
Edition James H. Stock
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Introduction to Econometrics, 4e (Stock/Watson)
Chapter 2 Review of Probability
2.1 Multiple Choice Questions
1) The probability of an outcome:
A) is the number of times that the outcome occurs in the long run.
B) equals M × N, where M is the number of occurrences and N is the population size.
C) is the proportion of times that the outcome occurs in the long run.
D) equals the sample mean divided by the sample standard deviation.
Answer: C
2) The probability of an event A or B (Pr(A or B)) to occur equals:
A) Pr(A) × Pr(B).
B) Pr(A) + Pr(B) if A and B are mutually exclusive.
C) .
D) Pr(A) + Pr(B) even if A and B are not mutually exclusive.
Answer: B
3) The cumulative probability distribution shows the probability:
A) that a random variable is less than or equal to a particular value.
B) of two or more events occurring at once.
C) of all possible events occurring.
D) that a random variable takes on a particular value given that another event has happened.
Answer: A
4) The expected value of a discrete random variable:
A) is the outcome that is most likely to occur.
B) can be found by determining the 50% value in the c.d.f.
C) equals the population median.
D) is computed as a weighted average of the possible outcome of that random variable, where
the weights are the probabilities of that outcome.
Answer: D
5) Let Y be a random variable. Then var(Y) equals:
A) .
B) E .
C) E .
D) E .
Answer: C
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6) The skewness of the distribution of a random variable Y is defined as follows:
A)
B) E
C)
D)
Answer: D
7) The skewness is most likely positive for one of the following distributions:
A) The grade distribution at your college or university.
B) The U.S. income distribution.
C) SAT scores in English.
D) The height of 18 year old females in the U.S.
Answer: B
8) The kurtosis of a distribution is defined as follows:
A)
B)
C)
D) E[(Y - )4)
Answer: A
9) For a normal distribution, the skewness and kurtosis measures are as follows:
A) 1.96 and 4
B) 0 and 0
C) 0 and 3
D) 1 and 2
Answer: C
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10) The conditional distribution of Y given X = x, Pr(Y = y =x), is:
A) .
B)
C)
D) .
Answer: D
11) The conditional expectation of Y given X, E(Y , is calculated as follows:
A)
B) E
C)
D) Pr(X = xi)
Answer: C
12) Two random variables X and Y are independently distributed if all of the following
conditions hold, with the exception of:
A) Pr(Y = y = x) = Pr(Y = y).
B) knowing the value of one of the variables provides no information about the other.
C) if the conditional distribution of Y given X equals the marginal distribution of Y.
D) E(Y) = E[E(Y )].
Answer: D
13) The correlation between X and Y:
A) cannot be negative since variances are always positive.
B) is the covariance squared.
C) can be calculated by dividing the covariance between X and Y by the product of the two
standard deviations.
D) is given by corr(X, Y) = .
Answer: C