Answer:
A. 0.1654
Explanation:
Let's call :
D: The event in which a person has a disease
ND: The event in which a person doesn't have a disease
TD: The event in which the test result is positive
Therefore, the probability that a person has the disease given that his test result is positive is calculated as:
P(D/TD) =P(D∩TD)/P(TD)
Where P(D∩TD) is the probability that a person has a disease and the test result is positive and P(TD) is the probability that the test result is positive.
So, The probability P(D∩TD) is calculated as a multiplication of:
P(D∩TD)=0.1% * 99% = 0.099%
Because 0.1% is the percentage of population that actually has the disease and 99% is the probability that the test detect the disease when it is present.
Then, for calculate the probability P(TD) we need to sum the probability of the following cases:
- The probability that a person has a disease and the test result is positive, that is P(D∩TD) and it is equal to 0.099%
- The probability that a person doesn't have a disease and the test result is positive, that is P(ND∩TD) and it is calculated as:
P(ND∩TD)= (100%-0.1%)*0.5%=0.4995%
Because (100%-0.1%) is the percentage of population that doesn't have the disease and 0.5% is the probability that the test imply that a person has the disease when it is not present.
So, P(TD) is calculated as:
P(TD) = P(D∩TD) + P(ND∩TD)
P(TD) = 0.099% + 0.4995%
P(TD) = 0.5985%
Finally, P(D/TD) is:
![P(D/TD) =(0.099%)/(0.5985%)=0.1654]()