3.2 Problems on Conditional Probability
Computing conditional probabilities from partial data, chaining them through the product rule, and reversing the conditioning with Bayes' theorem.
Applied Probability, 3.2 Problems on Conditional Probability
22 exercises
3.2 Exercise 1
Given the following data:
Determine, if possible, the conditional probability .
3.2 Exercise 2
In Exercise 11 from "Problems on Minterm Analysis," we have the following data: A survey of a represenative group of students yields the following information:
- 52 percent are male
- 85 percent live on campus
- 78 percent are male or are active in intramural sports (or both)
- 30 percent live on campus but are not active in sports
- 32 percent are male, live on campus, and are active in sports
- 8 perce…
3.2 Exercise 3
In a certain population, the probability a woman lives to at least seventy years is 0.70 and is 0.55 that she will live to at least eighty years. If a woman is seventy years old, what is the conditional probability she will survive to eighty years? Note that if then .
3.2 Exercise 4
From 100 cards numbered 00, 01, 02, , 99, one card is drawn. Suppose Ai is the event the sum of the two digits on a card is and Bj is the event the product of the two digits is j. Determine for each possible i.
3.2 Exercise 5
Two fair dice are rolled.
- What is the (conditional) probability that one turns up two spots, given they show different numbers?
- What is the (conditional) probability that the first turns up six, given that the sum is k, for each k from two through 12?
- What is the (conditional) probability that at least one turns up six, given that the sum is k, for each k from two through 12?
3.2 Exercise 6
Four persons are to be selected from a group of 12 people, 7 of whom are women.
- What is the probability that the first and third selected are women?
- What is the probability that three of those selected are women?
- What is the (conditional) probability that the first and third selected are women, given that three of those selected are women?
3.2 Exercise 7
Twenty percent of the paintings in a gallery are not originals. A collector buys a painting. He has probability 0.10 of buying a fake for an original but never rejects an original as a fake, What is the (conditional) probability the painting he purchases is an original?
3.2 Exercise 8
Five percent of the units of a certain type of equipment brought in for service have a common defect. Experience shows that 93 percent of the units with this defect exhibit a certain behavioral characteristic, while only two percent of the units which do not have this defect exhibit that characteristic. A unit is examined and found to have the characteristic symptom. What is the conditional prob…
3.2 Exercise 9
A shipment of 1000 electronic units is received. There is an equally likely probability that there are 0, 1, 2, or 3 defective units in the lot. If one is selected at random and found to be good, what is the probability of no defective units in the lot?
3.2 Exercise 10
Data on incomes and salary ranges for a certain population are analyzed as follows. event annual income is less than $25,000; event annual income is between $25,000 and $100,000; event annual income is greater than $100,000. event did not complete college education; event of completion of bachelor's degree; event of completion of graduate or professional degree program. Data may be ta…
3.2 Exercise 11
In a survey, 85 percent of the employees say they favor a certain company policy. Previous experience indicates that 20 percent of those who do not favor the policy say that they do, out of fear of reprisal. What is the probability that an employee picked at random really does favor the company policy? It is reasonable to assume that all who favor say so.
3.2 Exercise 12
A quality control group is designing an automatic test procedure for compact disk players coming from a production line. Experience shows that one percent of the units produced are defective. The automatic test procedure has probability 0.05 of giving a false positive indication and probability 0.02 of giving a false negative. That is, if D is the event a unit tested is defective, and T is the e…
3.2 Exercise 13
Five boxes of random access memory chips have 100 units per box. They have respectively one, two, three, four, and five defective units. A box is selected at random, on an equally likely basis, and a unit is selected at random therefrom. It is defective. What are the (conditional) probabilities the unit was selected from each of the boxes?
3.2 Exercise 14
Two percent of the units received at a warehouse are defective. A nondestructive test procedure gives two percent false positive indications and five percent false negative. Units which fail to pass the inspection are sold to a salvage firm. This firm applies a corrective procedure which does not affect any good unit and which corrects 90 percent of the defective units. A customer buys a unit fr…
3.2 Exercise 15
At a certain stage in a trial, the judge feels the odds are two to one the defendent is guilty. It is determined that the defendent is left handed. An investigator convinces the judge this is six times more likely if the defendent is guilty than if he were not. What is the likelihood, given this evidence, that the defendent is guilty?
3.2 Exercise 16
Show that if and , then . Is the converse true? Prove or give a counterexample.
3.2 Exercise 17
Since is a probability measure for a given B, we must have . Construct an example to show that in general .
3.2 Exercise 18
Use property (CP4) to show
3.2 Exercise 19
Show that .
3.2 Exercise 20
Show that .
3.2 Exercise 21
An individual is to select from among n alternatives in an attempt to obtain a particular one. This might be selection from answers on a multiple choice question, when only one is correct. Let A be the event he makes a correct selection, and B be the event he knows which is correct before making the selection. We suppose and . Determine ; show that and increases with n for fixed p.
3.2 Exercise 22
Polya's urn scheme for a contagious disease. An urn contains initially b black balls and r red balls (). A ball is drawn on an equally likely basis from among those in the urn, then replaced along with c additional balls of the same color. The process is repeated. There are n balls on the first choice, balls on the second choice, etc. Let Bk be the event of a black ball on the kth draw and Rk…
Adapted from Applied Probability © 2009 Paul E. Pfeiffer. Licensed under CC BY 3.0. Source: Applied Probability. Imported at revision d7a0420.