Answer:
0.6049
Step-by-step explanation:
Let's define the following events for a randomly selected person
HP: the person has the predisposition
NP: the person does not have the predisposition
TP: the person tests positive
TN: the person tests negative
We know that P(HP) = 0.03 (because 3% of people actually have the predisposition), so, P(NP) = 0.97,
P(TP | HP) = 0.99 (the genetic test is 99% accurate if a person has the predisposition),
P(TN | NP) = 0.98 (the genetic test is 99% accurate if a person does not have the predisposition),
P(TP | NP) = 0.02. We are looking for the probability that a randomly selected person who tests positive for the predisposition actually has the predisposition, i.e., P(HP | TP). By Bayes' formula
P(HP | TP) = (P(TP | HP)P(HP))/(P(TP | HP)P(HP) + P(TP | NP)P(NP)) = [(0.99)(0.03)]/[(0.99)(0.03) + (0.02)(0.97)] = 0.6049