1. À test for a certain disease is found to be 95% accurate, meaning that it will correctly diagnose the disease in 95 out of 100 people who have the ailment. The test is also 95% accurate for a negative result, meaning that it will correctly exclude the disease in 95 out of 100 people who do not have the ailment. For a certain segment of the population, the incidence of the disease is 4%. (1)r (Hint: define appropriate events and use Bayes Theorem): (2) person actually has the disease, given that the test is positive; (3) correct. Hence, You can conclude that there is only a much smaller probability to claim "the person really has the disease" after knowing that "the test is positive", though the test has 95% "correctness". Explain this difference. If a person tests positive, find the probability that the person actually has the disease Now suppose the incidence of the disease is 49%. Compute the probability that the The probability you obtained in (1) is much smaller than 0.95, if your computation is Medical Science

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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1. A test for a certain disease is found to be 95% accurate, meaning that it will correctly diagnose
the disease in 95 out of 100 people who have the ailment. The test is also 95% accurate for a
negative result, meaning that it will correctly exclude the disease in 95 out of 100 people who do
not have the ailment. For a certain segment of the population, the incidence of the disease is 4%.
(1)f
(Hint: define appropriate events and use Bayes Theorem):
(2)
person actually has the disease, given that the test is positive;
(3)
correct. Hence, You can conclude that there is only a much smaller probability to claim "the
person really has the disease" after knowing that "the test is positive", though the test has 95%
"correctness". Explain this difference.
If a person tests positive, find the probability that the person actually has the disease
Now suppose the incidence of the disease is 49°%. Compute the probability that the
The probability you obtained in (1) is much smaller than 0.95, if your computation is
Medical Science
De
EE
Hint.
Population: the segment of the population
Experiment: Determine whether or not a selected person has the disease
Outcomes: D, D (where D and D are defined below)
Sample space: S-(D, D}
Transcribed Image Text:Font Paragraph Styles VAILABLE Updates for Office are ready to be installed, but first we need to dlose some apps. Update now 1. A test for a certain disease is found to be 95% accurate, meaning that it will correctly diagnose the disease in 95 out of 100 people who have the ailment. The test is also 95% accurate for a negative result, meaning that it will correctly exclude the disease in 95 out of 100 people who do not have the ailment. For a certain segment of the population, the incidence of the disease is 4%. (1)f (Hint: define appropriate events and use Bayes Theorem): (2) person actually has the disease, given that the test is positive; (3) correct. Hence, You can conclude that there is only a much smaller probability to claim "the person really has the disease" after knowing that "the test is positive", though the test has 95% "correctness". Explain this difference. If a person tests positive, find the probability that the person actually has the disease Now suppose the incidence of the disease is 49°%. Compute the probability that the The probability you obtained in (1) is much smaller than 0.95, if your computation is Medical Science De EE Hint. Population: the segment of the population Experiment: Determine whether or not a selected person has the disease Outcomes: D, D (where D and D are defined below) Sample space: S-(D, D}
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