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If a test has a false positive rate of one in ten thousand, but only one in a million samples (or people) is a true positive, most of the "positives" detected by that test will be ...
The false positive paradox is a situation where the incidence of a condition is lower than the false positive rate of a test, and therefore, when the test indicates that a ...
A false positive, also known as a false detection or false alarm, occurs when an antivirus program detects a known virus string in an uninfected file. The file, while not ...
false positive. The erroneous identification of a threat or dangerous condition that turns out to be harmless. False positives often occur in intrusion detection systems.
false positive. n. A positive test result in a subject that does not possess the attribute for which the test is being conducted. false-pos·i·tive adj.
False-Positive Serologic Tests for Human T-Cell Lymphotropic Virus Type I Among Blood Donors Following Influenza Vaccination, 1992 . From October 31 through December 15, 1991, 10 ...
Corollary 3: If the prevalence of a condition is low, under 1 percent, even with high sensitivities and specificities, the likelihood of a positive test being false positive is ...
Of a statement, untrue. Falseness is used in proving propositions by considering the negative of the proposition to be true, then making deductions until a contradiction is reached ...
Subject: False positive result on a Urine Drug Screen Category: Science > Chemistry Asked by: jodiew64-ga List Price: $25.00: Posted: 22 Nov 2006 08:02 PST
A study of 161 prescription and over the counter medications showed that 65 of them produced false positive results in the most widely administered urine test.
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In statistics, the terms type I error (also, α error, false alarm rate (FAR) or false positive) and type II error (β error, or a false negative) are used to describe possible errors made in a statistical decision process. In 1928, Jerzy Neyman (1894-1981) and Egon Pearson (1895-1980), both eminent statisticians, discussed the problems associated with "deciding whether or not a particular sample may be judged as likely to have been randomly drawn from a certain population" (1928/1967, p.1), and identified "two sources of error", namely:

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