Based on the accuracy of the test and the probability of Kevin having the disease, the following are true:
- Probability that Kevin has diabetes and the test predicts this = 0.6375.
- Probability that Kevin has diabetes and the test doesn't predicts this = 0.1125.
- Probability that Kevin doesn't have diabetes and the test predicts this = 0.2125.
- Probability that Kevin doesn't have diabetes and the test doesn't predicts this = 0.0375.
<h3>Probability that Kevin has diabetes and the test predicts this</h3>
= Probability that Kevin has diabetes x Accuracy of test
= 0.75 x 0.85
= 0.6375
<h3>Probability that Kevin has diabetes and the test doesn't predicts this</h3>
= Probability that Kevin has diabetes x (1 - Accuracy of test )
= 0.75 x ( 1 - 0.85)
= 0.1125
<h3>Probability that Kevin doesn't have diabetes and the test predicts this</h3>
= Probability that Kevin doesn't have diabetes x Accuracy of test
= ( 1 - 0.75) x 0.85
= 0.2125
<h3>Probability that Kevin doesn't have diabetes and the test doesn't predicts this</h3>
= Probability that Kevin doesn't have diabetes x (1 - Accuracy of test )
= ( 1 - 0.75) x (1 - 0.85)
= 0.0375
In conclusion, the probability depends on the accuracy of the test and the probability of having diabetes.
Find out more on probability at brainly.com/question/6354635.
