Math 207 – Conditional Probability (General Multiplication Rule; Bayes’ Rule) Examples

Important Note: Although these problems illustrate the Law of Total Probability and Bayes’ Rule, you need not memorize the formula for the rule—in fact, I encourage you to solve each problem individually via a tree diagram.

 

  1. A bag contains 20 jelly beans: 5 black and 15 red beans. Two jelly beans are drawn at random and without replacement from the bag. Consider the events: A = {2 black jelly beans}, B = {exactly 1 black jelly bean}, and C = {0 black jelly beans}.
    1. Use counting methods (combinations—order unimportant) to find P(A), P(B), and P(C).

 

 

    1. Now use the general multiplication rule to determine P(A), P(B), and P(C). Do your answers agree? (They should.)

 

 

    1. Draw a complete tree diagram to illustrate your answer to part b. (Note: In the future, it’s fine for you to solve problems using a tree diagram as your argument—as long as the diagram is well-labeled, complete, and correct.)

 

 

 

  1. The probability of a certain disease is 0.01. A diagnostic test for the disease is developed. The test correctly diagnoses an infected person with probability 0.95. However, the test incorrectly diagnoses an uninfected patient with probability 0.06. If the test diagnoses a patient as having the disease, what is the conditional probability that the person really has the disease? Does this probability seem low? Why do you think that is?

 

 

 

 

 

 

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Law of Total Probablity

Suppose the events  are mutually exclusive and  (that is, the events “exhaust” the sample space). [Note: In the previous example, the mutually exclusive and exhaustive events were {disease} and {no disease}.]

 

Then for any event B,

 , where first we applied Axiom 3 for the probability of mutually exclusive events and then applied the multiplicative rule.

 

That is,  This is called the Law of Total Probability and it leads to another formula called Bayes’ Rule. You need not memorize these formulas, but you must understand the concept and be able to apply the general concept to a new problem—it’s fine to use a complete, well-documented tree diagram as your solution method.

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  1. About 99% of babies born in the United States survive. Furthermore, Caesarian section is used in about 20% of births. Given a Caesarian section is used, about 96% of babies survive (note that while the previous two numbers are fairly accurate, this number is actually made up). Now, given that a Caesarian section is not used, about what percent of babies survive? (Note: Now you’re looking for a probability within the tree diagram.)