Suppose that the reliability of a HIV test is specified as follows: Of people having HIV. 90% of the test detects the disease but 10% go undetected. Of people free of HIV, 99% of the test are judged HTV-ive but 1% are diagnosed as showing H3V+ive. From a large population of which only 0.1% have HIV one person is selected at random, given the HIV test, and the pathologist reports him/her as HIV+ive. What is the probability that the person actually has HIV?

Suppose that the reliability of a HIV test is specified as follows:Of people having HIV, 90% of the test detect the disease but 10% go undetected. Of people free of HIV, 99% of the test are judged HIV-ive but 1% are diagnosed as showing HIV+ive. From a large population of which only 0.1% have HIV, one person is selected at random, given the HIV test, and the pathologist reports him/her as HIV+ive. What is the probability that the person actually has HIV?

Suppose that the reliability of a HIV test is specified as follows: Of people having HIV, 90% of the test detect the disease but 10% go undetected. Of people free of HIV, 99% of the test are judged HIV–ive but 1% are diagnosed as showing HIV+ive. From a large population of which only 0.1% have HIV, one person is selected at random, given the HIV test, and the pathologist reports him/her as HIV+ive. What is the probability that the person actually has HIV?

Suppose that the reliability of a HIV test is specified as follows: Of people having HIV, 90% of the test detect the disease but 10% go undetected. Of people free of HIV, 99% of the test are judged HIV-ive but 1% are diagnosed as showing HIV+ive. From a large population of which only 0.1% have HIV, one person is selected at random, given the HIV test, and the pathologist reports "him" // "her" as HIV+ive. What is the probability that the person actually has HIV?

Suppose that the reliability of a HIV test is specified as follows: Of people having HIV, 90% of the test detect the disease but 10% go undetected. Of people free of HIV, 99% of the test are judged HIV-ive but 1% are diagnosed as showing HIV+ive. From a large population of which only 0.1% have HIV, one person is selected at random, given the HIV test, and the pathologist reports "him" // "her" as HIV+ive. What is the probability that the person actually has HIV?

Suppose that the reliability of a HIV test is speciflẹd as follows: Of people having HIV '90 %' of the test detect the disease but '10 %' go undetected. Of people free of HIV, '99 %' of the test are judged HIV-ive but '1 %' are diagnosed as showing HIV+ịve. From a large population of which only '0.1 %' have HIV, one person is selected at random, given the HIV, test, and the pathologist reports him/her as HIV+ive. What is the probatility that the person actually has HIV?

Suppose that the reliability of a HIV test is specified as follows. Of people having HIV, 90% of the test detect the diséase but 10% go undetected. Of people free of HIV, 99% of the test judged HIV (-ve) but 1% are diagnosed as showing HIV (+ ve). From a large population of which 0.1% have HIV, one person is selected at random, given the HIV test, and the pathologist report him/her as HIV (+ve) What is the probability that the person actually has HIV?

The reliability of a COVID PCR test is specified as follows Of people having COVID, 90% of the test detects the disease but 10% goes undetected. Of people free of COVID, 99% of the test is judged COVID negative but 1% are diagnosed as showing COVID positive. From a large population of which only 0.1% have COVID, one person is selected at random, given the COVID PCR test, and the pathologist reports him/her as COVID positive. Based on the above information, answer the following What is the probability of the ‘person to be tested as COVID positive’ given that ‘he is actually not having COVID’?