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YouTube T2-9 Bayes Theorem: Simple test for disease

Nicole Seaman

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Bayes Theorem updates a conditional probability with new evidence. In this case, the conditional probability (disease | positive test result) equals the joint probability (disease, positive test result) divided by the unconditional probability (positive test result). The question illustrated is from Chapter 6 of http://amzn.to/2C4UCo6 and it reads in full as follows: "Imagine there is a disease that afflicts just 1 in every 100 people in the population. A new test has been developed to detect the disease that is 99% accurate. That is, for people with the disease, the test correctly indicates that they have the disease in 99% of cases. Similarly, for those who do not have the disease, the test correctly indicates that they do not have the disease in 99% of cases. If a person takes the test and the result of the test is positive, what is the probability that he or she actually has the disease?"

Here is David's XLS: http://trtl.bz/2BO9LNq

 
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