Quant 1.14 05.05

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• A. negatively skewed.
• B. having no skewness.
• C. positively skewed.

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• A. 2.94%.
• B. 2.97%.
• C. 3.00%.

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• A. Portfolio P is 4.5%.
• B. Portfolio Q is 4.0%.
• C. Portfolio R is higher than its arithmetic mean annual return.

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• A. occurred more than 50% of the time.
• B. was less frequent than yen depreciation.
• C. in the 0.0 to 2.0 interval occurred 20% of the time.

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• A. 3% to 8%.
• B. 8% to 13%.
• C. 13% to 18%.

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• A. 5 .
• B. 4 .
• C. 3 .

Q. Which probability estimate most likely varies greatly between people?

• A. An a priori probability
• B. An empirical probability
• C. A subjective probability

If two events, A and B, are independent, and the probability of A does not equal the probability of B [i.e., P(A) ≠ P(B)], then the probability of event A given that event B has occurred [i.e., P(A | B)] is best described as:

• A. P(A).
• B. P(B).
• C. P(B | A).

Q. Which of the following correlation coefficients indicates the weakest linear relationship between two variables?

• A. –0.67
• B. –0.24
• C. 0.33

Q. In a typical year, 5% of all CEOs are fired for “performance” reasons. Assume that CEO performance is judged according to stock performance and that 50% of stocks have above-average returns or “good” performance. Empirically, 30% of all CEOs who were fired had “good” performance. Using Bayes’ formula, what is the probability that a CEO will be fired given “good” performance? (Hint, let P(A) be the probability of a CEO being fired, P(B) be the probability of a “good” performance rating, P(B | A) be the likelihood of a “good” performance rating given that the CEO was fired, and P(A | B) be the likelihood of the CEO being fired given a “good” performance rating.)

• A. 1.5%.
• B. 2.5%.
• C. 3.0%.