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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]
For a Type I error, it is shown as α (alpha) and is known as the size of the test and is 1 minus the specificity of the test. This quantity is sometimes referred to as the confidence of the test, or the level of significance (LOS) of the test. For a Type II error, it is shown as β (beta) and is 1 minus the power or 1 minus the sensitivity of ...
The specificity of the test is equal to 1 minus the false positive rate. In statistical hypothesis testing, this fraction is given the Greek letter α, and 1 − α is defined as the specificity of the test. Increasing the specificity of the test lowers the probability of type I errors, but may raise the probability of type II errors (false ...
In quality management, a nonconformity (sometimes referred to as a non conformance or nonconformance or defect) is a deviation from a specification, a standard, or an expectation. Nonconformities or nonconformance can be classified in seriousness multiple ways, though a typical classification scheme may have three to four levels, including ...
A product defect is any characteristic of a product which hinders its usability for the purpose for which it was designed and manufactured. Product defects arise most prominently in legal contexts regarding product safety , where the term is applied to "anything that renders the product not reasonably safe". [ 1 ]
Similarly, typewriter repair people used to refer to "a loose nut behind the keyboard" or a "defective keyboard controller." The broadcast engineering or amateur radio version is referred to as a "short between the headphones". Another term used in public safety two-way radio (i.e. police, fire, ambulance, etc.) is a "defective PTT button ...
A defect can be defined as a nonconformance of a quality characteristic (e.g. strength, width, response time) to its specification. DPMO is stated in opportunities per million units for convenience: processes that are considered highly capable (e.g., processes of Six Sigma quality) are those that experience fewer than 3.4 defects per million ...
In linear algebra, a defective matrix is a square matrix that does not have a complete basis of eigenvectors, and is therefore not diagonalizable. In particular, an n × n {\displaystyle n\times n} matrix is defective if and only if it does not have n {\displaystyle n} linearly independent eigenvectors. [ 1 ]