In a laboratory, a test was discovered to detect a certain disease.
The effectiveness of this test is known as follows: if we denote by E the event that a patient have the disease and for N the event that the test is negative, then it is known that (c|) = 0.92, (N|c) = 0.93,() = 0.01
Obtain the probabilities (|) and (|).
Approach: I've tried to decompose the given data but I havent been able to get any other value. Just that P(Ec) = 0.99
Note:the c next to the characters is "complement"
Thanks.
Bayes's theorem in general says:
$$P(A|B) = \frac{P(B|A) * P(A)}{P(B)}$$
So, to get $P(E|N)$:
$$P(E|N) = \frac{P(N|E) * P(E)}{P(N)}$$
You have $P(N|E)$ and $P(E)$. What is $P(N)$?
$P(N) = P(N\cap E) + P(N \cap E^C) = P(N|E)*P(E) + P(N|E^C)*P(E^C)$
And you have all those values as well, so now you can figure out $P(N)$ and thus $P(E|N)$.
Do something similar for $P(E^C|N)$