Calculus Applied to Probability and Statistics
by
Stefan Waner and Steven R. Costenoble

Exercises
for
Section 2: Probability Density Functions: Uniform, Exponential, Normal, and Beta

1. Continuous Random Variables and Histograms 2. Probability Density Functions: Uniform, Exponential, Normal, and Beta 3. Mean, Median, Variance and Standard Deviation Calculus and Probability Main Page "Real World" Page
Answers to Odd-Numbered Exercises

In Exercises 19-28, say which kind of probability density function is most appropriate for the given random variable: uniform, exponential, normal, or beta.

Applications

Unless otherwise stated, round answers to all applications to four decimal places.

31. Boring Television Series Your company's new series "Avocado Comedy Hour" has been a complete flop, with viewership continuously declining at a rate of 30% per month. Use a suitable density function to calculate the probability that a randomly chosen viewer will be lost sometime in the next three months.

32. Bad Investments Investments in junk bonds are declining continuously at a rate of 5% per year. Use a suitable density function to calculate the probability that a dollar invested in junk bonds will be pulled out of the junk bond market within the next two years.

33. Radioactive Decay The half-life of Carbon-14 is 5,730 years. What is the probability that a randomly selected Carbon-14 atom will not yet have decayed in 4,000 years' time?

34. Radioactive Decay The half-life of Plutonium-239 is 24,400 years. What is the probability that a randomly selected Plutonium-239 atom will not yet have decayed in 40,000 years' time?

35. The Doomsday Meteor The probability that a "doomsday meteor" will hit the earth in any given year and release a billion megatons or more of energy is on the order of 0.000 000 01.

Source: NASA International Near-Earth-Object Detection Workshop (The New York Times, January 25, 1994, p. C1.)

36. Galactic Cataclysm The probability that the galaxy MX-47 will explode within the next million years is estimated to be 0.0003.

Exercises 37-44 use the normal probability density function and require either the use of technology for numerical integration or a table of values of the standard normal distribution.

Cumulative Distribution If f is a probability density function defined on the interval (a, b), then the cumulative distribution function F is given by

Communication and Reasoning Exercises

55. Why is a probability density function often more convenient than a histogram?

56. Give an example of a probability density function that is increasing everywhere on its domain.

57. Give an example of a probability density function that is concave up everywhere on its domain.

58. Suppose that X is a normal random variable with mean µ and standard deviation , and that Z is a standard normal variable. Using the substitution z = (x µ)/ in the integral, show that

59. Your friend thinks that if f is a probability density function for the continuous random variable X, then f(a) is the probability that X = a. Explain to your friend why this is wrong.

60. Not satisfied with your explanation in the previous exercise, your friend then challenges you by asking, "If f(a) is not the probability that X = a, then just what does f(a) signify?" How would you respond?

61. Your friend now thinks that if F is a cumulative distribution function for the continuous random variable X, then F(a) is the probability that X = a. Explain why your friend is still wrong.

62. Once again not satisfied with your explanation in the previous exercise, your friend challenges you by demanding, "If F(a) is not the probability that X = a, then just what does F(a) signify?" How would you respond?

1. Continuous Random Variables and Histograms 2. Probability Density Functions: Uniform, Exponential, Normal, and Beta 3. Mean, Median, Variance and Standard Deviation Calculus and Probability Main Page "Real World" Page
Answers to Odd-Numbered Exercises

We would welcome comments and suggestions for improving this resource. Mail us at:
Stefan Waner (matszw@hofstra.edu) Steven R. Costenoble (matsrc@hofstra.edu)
Last Updated: September, 1996
Copyright © 1996 StefanWaner and Steven R. Costenoble