Answer:
a) P₁ = 0,0294
b) P₂ = 0,097
c) P₃ = 0,1264
P₃ is the total probability of the individual having a positive test result
d) P₄ = 0,232
Explanation:
a) Probability that an individual has the disease and has a positive result is P₁ :
P₁ = The probability of having the disease * Probability of + in the test result
P₁ = 0,03 * 0,98
P₁ = 0,0294
b) the probability that an individual does not have the disease and has a positive test result P₂ is:
P₂ = 0,97 * 0,1
P₂ = 0,097
c) P₃ the sum of the two previous probabilities is:
P₃ = 0,0294 + 0,097
P₃ = 0,1264
P₃ is the total probability of the individual having a positive test result
d) Applying the Bayes theorem we can get the probability that an individual with a positive test result has the disease. (P₄ )
Bayes theorem establishes:
P [ A/B ] = P[B/A] * P(A) / P(B)
In this case
P[ with disease/ given (+)tr]
= P [(+)Test/ with disease]* P (with disease)/ P of test +
P₄ = 0,98 * 0,03 / 0,1264
P₄ = 0,232