A certain virus infects one in every 300 people. A test used to detect the virus...
A certain virus infects one in every 300 people. A test used to detect the virus in a person is positive 80% of the time when the person has the virus and 15 %
of the time when the person does not have the virus. (This 15 % result is called a false positive.)
Let A be the event "the person is infected" and B be the event "the person tests positive."
(a) Using Bayes' Theorem, when a person tests positive, determine the probability that the person is infected.
(b) Using Bayes' Theorem, when a person tests negative, determine the probability that the person is not infected.
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A certain virus infects one in every 300 people. A test used to
detect the virus...
A certain virus infects one in every 250 people. A test used to detect the virus...
A certain virus infects one in every 250 people. A test used to detect the virus in a person is positive 80% of the time when the person has the virus and 15% of the time when the person does not have the virus. (This 15% result is called a false positive) Let A be the event "the person is infected" and B be the event "the person tests positive." (a) Using Bayes' Theorem, when a person tests positive, determine...
A certain virus infects one in every 300 people. A test used to detect the virus...
A certain virus infects one in every 300 people. A test used to detect the virus in a person is positive 90% of the time when the person has the virus and 15% of the time when the person does not have the virus. (This 15% result is called a false positive.) Let A be the event the person is infected" and B be the event the person tests positive." (a) Using Bayes' Theorem, when a person tests positive, determine...
A certain virus infects one in every 300 people. A test used to detect the virus...
A certain virus infects one in every 300 people. A test used to detect the virus in a person is positive 80% of the time if the person has the virus and 5% of the time if the person does not have the virus. (This 5% result is called a false positive.) Let A be the event "the person is infected" and B be the event "the person tests positive". a) Find the probability that a person has the virus...
A certain virus infects one in every 500 people. A test used to detect the virus...
A certain virus infects one in every 500 people. A test used to detect the virus in a person is positive 90% of the time if the person has the virus and 10% of the time if the person does not have the virus. Let A be the event "the person is infected" and B be the event "the person tests positive." (a) Find the probability that a person has the virus given that they have tested positive. (b)...
A certain virus infects one in every 200 people. A test used to detect the virus...
A certain virus infects one in every 200 people. A test used to detect the virus in a person is positive 80% of the time if the person has the virus and 5% of the time if the person does not have the virus. Using Bayes' Rule, if a person tests positive, determine the probability the person has the virus. Round to four decimal places.
Problem 7. A certain virus infects five in every 100 people. A test used to detect...
Problem 7. A certain virus infects five in every 100 people. A test used to detect the virus in a person is positive 70% of the time if the person has the virus, and 9% of the time if the person does not have the virus. Using the Bayes’s theorem, if a person tests positive, determine the probability that the person is infected.
A certain virus infects one in every 200 people. A test used to detect the virus in a person is positive 90% of the tim...
A certain virus infects one in every 200 people. A test used to detect the virus in a person is positive 90% of the time if the person has the virus and 8% of the time if the person does not have the virus. (This 8% result is called a false positive.) Let A be the event "the person is infected" and B be the event "the person tests positive". a) Find the probability that a person has the virus...
2 pts 1 Details < > Question 16 A certain virus infects one in every 300...
2 pts 1 Details < > Question 16 A certain virus infects one in every 300 people. A test used to detect the virus in a person is positive 80% of the time if the person has the virus and 8% of the time if the person does not have the virus. (This 8% result is called a false positive.) Let A be the event the person is infected" and B be the event "the person tests positive". a) Find...
RBV testing Suppose that 1% of all people are infected with the rare banana virus (RBV)....
RBV testing Suppose that 1% of all people are infected with the rare banana virus (RBV). There is a test to detect the RBV: if you do have the RBV, then the test will correctly detect this 99% of the time; if you do not have RBV, then the test will correctly indicate this 97% of the time. We assume that if the RBV test is given repeatedly to the same person, then the test results are independent of cach...
The probability of a randomly selected adult in one country being infected with a certain virus...
The probability of a randomly selected adult in one country being infected with a certain virus is 0.006. In tests for the virus, blood samples from 19 people are combined. What is the probability that the combined sample tests positive for the virus? Is it unlikely for such a combined sample to test positive? Note that the combined sample tests positive if at least one person has the virus.
A certain virus infects one in every 300 people. A test used to detect the virus in a person is positive 90% of the time when the person has the virus and 15% of the time when the person does not have the virus. (This 15% result is called a false positive.) Let A be the event the person is infected" and B be the event the person tests positive." (a) Using Bayes' Theorem, when a person tests positive, determine...
A certain virus infects one in every 200 people. A test used to detect the virus in a person is positive 80% of the time if the person has the virus and 5% of the time if the person does not have the virus. Using Bayes' Rule, if a person tests positive, determine the probability the person has the virus. Round to four decimal places.
A certain virus infects one in every 200 people. A test used to detect the virus in a person is positive 90% of the time if the person has the virus and 8% of the time if the person does not have the virus. (This 8% result is called a false positive.) Let A be the event "the person is infected" and B be the event "the person tests positive". a) Find the probability that a person has the virus...
2 pts 1 Details < > Question 16 A certain virus infects one in every 300 people. A test used to detect the virus in a person is positive 80% of the time if the person has the virus and 8% of the time if the person does not have the virus. (This 8% result is called a false positive.) Let A be the event the person is infected" and B be the event "the person tests positive". a) Find...
RBV testing Suppose that 1% of all people are infected with the rare banana virus (RBV). There is a test to detect the RBV: if you do have the RBV, then the test will correctly detect this 99% of the time; if you do not have RBV, then the test will correctly indicate this 97% of the time. We assume that if the RBV test is given repeatedly to the same person, then the test results are independent of cach...
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