P(A) = 1/200 = 0.005
P(B | A) = 0.9
P(B | A') = 0.08
a) P(B) = P(B | A) * P(A) + P(B | A') * P(A') = 0.9 * 0.005 + 0.08 * (1 - 0.005) = 0.0841
P(A | B) = P(B | A) * P(A) / P(B) = 0.9 * 0.005 / 0.0841 = 0.054 = 5.4%
b) P(B') = 1 - P(B) = 1 - 0.0841 = 0.9159
P(B' | A') = 1 - P(B | A') = 1 - 0.08 = 0.92
P(A' | B') = P(B' | A') * P(A') / P(B') = 0.92 * (1 - 0.005) / 0.9159 = 0.999 = 99.9%
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 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...
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...
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 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...
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 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.
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