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An approach to investigations designed to recognize a particular medical condition in the large population, usually by means of a blood test, which might result in the considerable saving in the number of tests carried out. In its place of testing each person separately, blood samples from, k people are pooled and analysed jointly. If the test is negative, this test clears k people. If the test is positive in nature then each of the k individual blood samples should be tested separately, and in all k 1 tests are needed for these k people. If the probability of the positive test (p) is less, the scheme is likely to give the outcome in far fewer tests being essential. For instance, if p 0:01, it can be shown that the value of k minimizes the expected number of tests per person is 11, and that expected number of the tests is 0.2, resulting in 80%saving in the number of tests compared with the testing each and every individual separately.
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