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A false negative error, or false negative, is a test result which wrongly indicates that a condition does not hold. For example, when a pregnancy test indicates a woman is not pregnant, but she is, or when a person guilty of a crime is acquitted, these are false negatives.
Accuracy is also used as a statistical measure of how well a binary classification test correctly identifies or excludes a condition. That is, the accuracy is the proportion of correct predictions (both true positives and true negatives) among the total number of cases examined. [10]
In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false. [1] Type I error: an innocent person may be convicted. Type II error: a guilty person may be not convicted.
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.
Fundamental attribution error, the tendency for people to overemphasize personality-based explanations for behaviors observed in others while under-emphasizing the role and power of situational influences on the same behavior [115] (see also actor-observer bias, group attribution error, positivity effect, and negativity effect).
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TestingCup – Polish Championship in Software Testing, Katowice, May 2016 Software testing is the act of checking whether software satisfies expectations.. Software testing can provide objective, independent information about the quality of software and the risk of its failure to a user or sponsor.
Manifest Your Goals. Taking time on New Year's Eve to truly meditate and reflect on the year ahead is an excellent way to head into the new year with a focused, clear mindset.Try breaking your ...