Chapter 4: Q169SE (page 281)
The random variable xhas a normal distribution withand . Find the following probabilities:
a.
b.
c.
d.
e.
f.
Short Answer
a.
b.
c.
d.
e.
f.
Chapter 4: Q169SE (page 281)
The random variable xhas a normal distribution withand . Find the following probabilities:
a.
b.
c.
d.
e.
f.
a.
b.
c.
d.
e.
f.
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Get started for freeInvestment risk analysis. The risk of a portfolio of financial assets is sometimes called investment risk. In general, investment risk is typically measured by computing the variance or standard deviation of the probability distribution that describes the decision maker’s potential outcomes (gains or losses). The greater the variation in potential outcomes, the greater the uncertainty faced by the decision maker; the smaller the variation in potential outcomes, the more predictable the decision maker’s gains or losses. The two discrete probability distributions given in the next table were developed from historical data. They describe the potential total physical damage losses next year to the fleets of delivery trucks of two different firms.
Firm A | Firm B | |||||
Loss Next Year | Probabiity | Loss Next Year | Probability | |||
0 | 0.01 | 0 | 0 | |||
500 | 0.01 | 200 | 0.01 | |||
1000 | 0.01 | 700 | 0.02 | |||
1500 | 0.02 | 1200 | 0.02 | |||
2000 | 0.35 | 1700 | 0.15 | |||
2500 | 0.3 | 2200 | 0.3 | |||
3000 | 0.25 | 2700 | 0.3 | |||
3500 | 0.02 | 3200 | 0.15 | |||
4000 | 0.01 | 3700 | 0.02 | |||
4500 | 0.01 | 4200 | 0.02 | |||
5000 | 0.01 | 4700 | 0.01 |
a. Verify that both firms have the same expected total physical damage loss.
b. Compute the standard deviation of each probability distribution and determine which firm faces the greater risk of physical damage to its fleet next year.
4.133 Suppose xis a random variable best described by a uniform
probability distribution with c= 20 and d= 45.
a. Find f(x)
b. Find the mean and standard deviation of x.
c. Graph f (x) and locate and the interval onthe graph. Note that the probability that xassumes avalue within the interval is equal to 1.
Buy-side vs. sell-side analysts’ earnings forecasts. Financial analysts who make forecasts of stock prices are categorized as either “buy-side” analysts or “sell-side” analysts. Refer to the Financial Analysts Journal (July/August 2008) comparison of earnings forecasts of buy-side and sell-side analysts, Exercise 2.86 (p. 112). The mean and standard deviation of forecast errors for both types of analysts are reproduced in the table. Assume that the distribution of forecast errors are approximately normally distributed.
a. Find the probability that a buy-side analyst has a forecast error of +2.00 or higher.
b. Find the probability that a sell-side analyst has a forecast error of +2.00 or higher
Buy-Side Analysts | Sell-Side Analysts | |
Mean | 0.85 | -0.05 |
Standard Deviation | 1.93 | 0.85 |
How many questionnaires to mail? The probability that a consumer responds to a marketing department’s mailed questionnaire is 0.4. How many questionnaires should be mailed if you want to be reasonably certain that at least 100 will be returned?
Blood diamonds. According to Global Research News (March 4, 2014), one-fourth of all rough diamonds produced in the world are blood diamonds, i.e., diamonds mined to finance war or an insurgency. (See Exercise 3.81, p. 200.) In a random sample of 700 rough diamonds purchased by a diamond buyer, let x be the number that are blood diamonds.
a. Find the mean of x.
b. Find the standard deviation of x.
c. Find the z-score for the value x = 200.
d. Find the approximate probability that the number of the 700 rough diamonds that are blood diamonds is less than or equal to 200.
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