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Chance Rules pp 87-104 | Cite as

Conditional Probability and the Reverend Thomas Bayes

  • Brian Everitt
Chapter

Introduction

Suppose you have two dice and are idly speculating on the chances of rolling one and getting a six and then rolling the other and finding the result is an even number. Because the result of the second throw in no way depends on the result of the first, the two events are independent. Thus, as we have seen in Chapter  2, the probability of both happening is simply the product of the probabilities of each separate event—that is,
$$\text{Pr(six \ with\ first\ die\ and \ even \ number \ with \ second)} = \frac{1}{6}\times \frac{3}{6} = \frac{3}{36} = \frac{1}{12}$$

Keywords

Breast Cancer Conditional Probability Positive Test Colour Blindness Unconditional Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.King’s College, School of MedicineLondonUK

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