2 pts 1 Details < > Question 16 A certain virus infects one in every 300...
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 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...
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 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 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 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 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 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.
Over for bonus question® 2. (+10) The reliability of a particular test for the Ebola virus is as follows: If the subject has Ebola, the test comes back positive of the time. If the subject does not have Ebola, the test res back positive 1% of the time. From a large population, in which 2 in every 10,000 people have Ebola, a person is selected at random and given the test, which comes back positive. SHOW ALL WORK AND CIRCLE...
1. For the choirmaster. A psalm of David. 2. Hear.my.troubles, O God. Kesp.me.safe from terror, The Department of Health of a certain state estimates a 10% rate of HIV for the general population Tests for HIV are 95% accurate in detecting both true negatives and true positives. Random see 5000 "at risk people and 20,000 people from the general population results in the following table. Use the table below to complete parts (a) through (e). at risk population and a...