A study concluded that among people with a certain virus, 99.2% of tests conducted were (correctly) positive, while for people without the virus, 97.9% of the tests were (correctly) negative. If 32% of patients actually carry the virus, what's the probability that a patient testing negative is truly free of the virus?

Following are the solution to the question:

Step-by-step explanation:

The probability of virus  P(V) =0.32  

No virus  P(NV) =0.66

Patient testing of negative P(TN) = virus, and negative testing+no virus and negative testing

This is why the likelihood of a patient being free of the virus is negative.

answer:      

step-by-step explanation:

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