A certain virus infects one in every 250 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 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. Click the icon to the right to review Bayes' Theorem. (a) The probability that a person is infected when a person tests positive is . (Do not round until final answer. Then round to three decimal places as needed.)