A certain affects virus 0.4% of the population (in a population of 100,000 people, 400 will be infected with the virus). A test used to detect the virus in a person is positive 87% of the time if the person has the virus (true positive) and it is positive 14% of the time if the person does not have the virus (false positive). Fill in the remainder of the following table and use it to answer the questions below. Infected Not Infected Total Positive Test Negative Test Total 400 99,600 100,000 Round all percents to the nearest tenth of a percent as needed. a) Examine the "Positive Test" row of the table. If a person tests positive for the virus, what is the probability that the person is really infected. (Note: in medical terminology, this probability measures the "positive predictive value" of the test) b) If a person tests negative for the virus, what is the probability that the person really is not infected. (This is called the "negative predictive value")

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A certain affects virus 0.4% of the population (in a population of 100,000 people, 400 will be infected with
the virus). A test used to detect the virus in a person is positive 87% of the time if the person has the virus
(true positive) and it is positive 14% of the time if the person does not have the virus (false positive). Fill in
the remainder of the following table and use it to answer the questions below.
Infected
Not Infected
Total
Positive Test
Negative Test
Total
400
99,600
100,000
Round all percents to the nearest tenth of a percent as needed.
a) Examine the "Positive Test" row of the table. If a person tests positive for the virus, what is the
probability that the person is really infected.
(Note: in medical terminology, this probability measures the "positive predictive value" of the test)
b) If a person tests negative for the virus, what is the probability that the person really is not infected.
(This is called the "negative predictive value")
Transcribed Image Text:A certain affects virus 0.4% of the population (in a population of 100,000 people, 400 will be infected with the virus). A test used to detect the virus in a person is positive 87% of the time if the person has the virus (true positive) and it is positive 14% of the time if the person does not have the virus (false positive). Fill in the remainder of the following table and use it to answer the questions below. Infected Not Infected Total Positive Test Negative Test Total 400 99,600 100,000 Round all percents to the nearest tenth of a percent as needed. a) Examine the "Positive Test" row of the table. If a person tests positive for the virus, what is the probability that the person is really infected. (Note: in medical terminology, this probability measures the "positive predictive value" of the test) b) If a person tests negative for the virus, what is the probability that the person really is not infected. (This is called the "negative predictive value")
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