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Published online before print November 21, 2002, 10.1148/radiol.2261011712

(Radiology 2003;226:12.)

A more recent version of this article appeared on January 1, 2003
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© RSNA, 2002

Statistical Concepts Series

Probability in Radiology1

Elkan F. Halpern, PhD and G. Scott Gazelle, MD, MPH, PhD

1 From the DATA Group, Department of Radiology, Massachusetts General Hospital, Zero Emerson Pl, Suite 2H, Boston, MA 02114. Received October 19, 2001; revision requested December 26; revision received March 27, 2002; accepted April 9. Address correspondence to E.F.H. (e-mail: elk@the-data-group.org).

In this article, a summary of the basic rules of probability using examples of their application in radiology is presented. Those rules describe how probabilities may be combined to obtain the chance of "success" with either of two diagnostic or therapeutic procedures or with both. They define independence and relate it to the conditional probability. They describe the relationship (Bayes rule) between sensitivity, specificity, and prevalence on the one hand and the positive and negative predictive values on the other. Finally, the two distributions most commonly encountered in statistical models of radiologic data are presented: the binomial and normal distributions.

© RSNA, 2002

Index terms: Statistical analysis




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