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 1 through 12, check whether the given function is a probability density function. If a function fails to be a probability density function, say why.

In Exercises 13-18, find the values of $k$ for which the given functions are probability density functions.

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.

29. Salaries Assuming that workers' salaries in your company are uniformly distributed between $10,000 and $40,000 per year, find the probability that a randomly chosen worker earns an annual salary between $14,000 and $20,000.

30. Grades The grade point averages of members of the Gourmet Society are uniformly distributed between 2.5 and 3.5. Find the probability that a randomly chosen member of the society has a grade point average between 3 and 3.2.

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 $σ,$ and that $Z$ is a standard normal variable. Using the substitution $z = (x - µ)/σ$ 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 probability density 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