Patients of a clinic are tested for a particular desease. For each patient, the result of the test – ‘infected’/’not infected’ – is correct with the probability 0.8. Suppose that 20% of the patients are infected. What is the probability that a given patient is indeed infected if his/her test result shows ‘infected’?
◦ 0.4 ◦ 0.5 ◦ 0.6 ◦ 0.64 ◦ 0.8
I suppose the answer is 0.8 since that is the probability that a result is accurate.
If test shows "infected", then it is positive
If test shows "not infected", then it is negative
P(positive/infected)=0.80
P(negative/not infected)=0.80
P(positive/not infected)=1-0.80=0.20
P(infected)=0.20
P(not infected)=1-0.20=0.80
So,
P(positive)=P(positive/infected) "\\times" P(infected)+P(positive/not infected) "\\times" P(not infected)
"=0.80 \\times 0.20+0.20 \\times 0.80 \\\\\n\n=0.32"
Using Bayes rule:
"P(infected\/positive)=P(positive\/infected) \\times \\frac{P(infected)}{P(positive)} \\\\\n\n=0.80 \\times \\frac{0.20}{0.32} \\\\\n\n=0.5"
The answer is 0.5
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