Talk:Pre- and post-test probability: Difference between revisions

Revision as of 05:54, 1 November 2016

Revision as of 14:30, 11 May 2019

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But that can be read directly off of the chart given in the article, in one calculation, by the definition of conditional probability:

:<math> P( Cancer = True | Test = True) = \frac{ P(Cancer = True \andland Test = True)}{P(Test=True)} = \frac{2}{2+8} = 0.10</math>

That seems '''way''' easier than the complicated multi-step process described in the example. So why would you ever do it that way?