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Let's have a fun way to learn Conditional Probabilities and Bayes' Theorem Here's a story problem about a situation that doctors often encounter: 1% of women at age forty who participate in routine screening have breast cancer.  80% of women with breast cancer will get positive mammographies.  9.6% of women without breast cancer will also get positive mammographies.  A woman in this age group had a positive mammography in a routine screening.  What is the probability that she actually has breast cancer? What do you think the answer is?  If you haven't encountered this kind of problem before, please take a moment to come up with your own answer before continuing. http://yudkowsky.net/bayes/bayes.html [´ËÌù×ÓÒѾ­±»×÷ÕßÓÚ2005-11-9 22:59:01±à¼­¹ý]    Êղؠ  ·ÖÏí   ¶¥(0)

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80% of women with breast cancer will get positive mammographies thus 20% women wont.. 9.6% of women without cancer will have positive thus 93.4% of them wont have ... it should be clear if we simply draw the diagram to represent the relationship...              80% have cancer  ( positive)       1%  ----<              20% have cancer   (nagative)                     9.6% no cancer ( positive) 99%----<              93.4% no cancer ( nagative) then ? whats next >? I got confused ... if the result is positive... she has 0.01*0.08 / ( 0.01*0.08 + 0.99*0.096) .. am I right ? almost the conditional probability ...

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Don't get confused. If you keep reading on that website you will have a very clear picture.