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Theories of test reliability have been developed to estimate the effects of inconsistency on the accuracy of measurement. The basic starting point for almost all theories of test reliability is the idea that test scores reflect the influence of two sorts of factors: [ 7 ]
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] As such, it compares estimates of pre- and post-test probability.
For databases reliability, availability, scalability and recoverability (RASR), is an important concept. Atomicity, consistency, isolation (sometimes integrity), durability is a transaction metric. When dealing with safety-critical systems, the acronym reliability, availability, maintainability and safety is frequently used.
The source reliability is rated between A (history of complete reliability) to E (history of invalid information), with F for source without sufficient history to establish reliability level. The information content is rated between 1 (confirmed) to 5 (improbable), with 6 for information whose reliability can not be evaluated.
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).
Reliability may be closely related to performance. For instance, a product specification may define parameters for up-time, or acceptable failure rates. Reliability is a major contributor to brand or company image, and is considered a fundamental dimension of quality by most end-users.
A variety of methods exist for human reliability analysis (HRA). [ 3 ] [ 4 ] Two general classes of methods are those based on probabilistic risk assessment (PRA) and those based on a cognitive theory of control .
Bayes' theorem confers inherent limitations on the accuracy of screening tests as a function of disease prevalence or pre-test probability. It has been shown that a testing system can tolerate significant drops in prevalence, up to a certain well-defined point known as the prevalence threshold , below which the reliability of a positive ...