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  2. Negative testing - Wikipedia

    en.wikipedia.org/wiki/Negative_testing

    Negative testing is a method of testing an application or system to improve the likelihood that an application works as intended/specified and can handle unexpected input and user behavior. [1] Invalid data is inserted to compare the output against the given input.

  3. False positives and false negatives - Wikipedia

    en.wikipedia.org/wiki/False_positives_and_false...

    Complementarily, the false negative rate (FNR) is the proportion of positives which yield negative test outcomes with the test, i.e., the conditional probability of a negative test result given that the condition being looked for is present. In statistical hypothesis testing, this fraction is given the letter β.

  4. Negative test - Wikipedia

    en.wikipedia.org/wiki/Negative_test

    A negative test can relate to: Negative diagnostic test, a medical test in which the target parameter that was evaluated was not present; Negative test variation, a software stress test designed to determine the response of the system outside of normal parameters; Negative testing

  5. You can still be contagious with COVID if you have a negative ...

    www.aol.com/news/still-contagious-covid-negative...

    If that test is negative, test again another 48 hours later. The emergence of new variants, in particular JN.1 , has not affected the accuracy of at-home tests, TODAY.com previously reported.

  6. Positive and negative predictive values - Wikipedia

    en.wikipedia.org/wiki/Positive_and_negative...

    The negative predictive value is defined as: = + = where a "true negative" is the event that the test makes a negative prediction, and the subject has a negative result under the gold standard, and a "false negative" is the event that the test makes a negative prediction, and the subject has a positive result under the gold standard.

  7. Type I and type II errors - Wikipedia

    en.wikipedia.org/wiki/Type_I_and_type_II_errors

    In statistical hypothesis testing, a type I error, or a false positive, is the erroneous rejection of a true null hypothesis. A type II error, or a false negative, is the erroneous failure in bringing about appropriate rejection of a false null hypothesis. [1]

  8. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    A negative result in a test with high sensitivity can be useful for "ruling out" disease, [4] since it rarely misdiagnoses those who do have the disease. A test with 100% sensitivity will recognize all patients with the disease by testing positive. In this case, a negative test result would definitively rule out the presence of the disease in a ...

  9. Dental pulp test - Wikipedia

    en.wikipedia.org/wiki/Dental_pulp_test

    Dental pulpal testing is a clinical and ... the degree of inflammation or innervation cannot be inferred from these tests. False positive or false negative results ...