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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 negatives that reject the alternative hypothesis when it is true). [a]
Measurement uncertainty. In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a quantity measured on an interval or ratio scale. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty ...
Laboratory quality control is designed to detect, reduce, and correct deficiencies in a laboratory's internal analytical process prior to the release of patient results, in order to improve the quality of the results reported by the laboratory. Quality control (QC) is a measure of precision, or how well the measurement system reproduces the ...
Student's t-test is a statistical test used to test whether the difference between the response of two groups is statistically significant or not. It is any statistical hypothesis test in which the test statistic follows a Student's t -distribution under the null hypothesis. It is most commonly applied when the test statistic would follow a ...
Medical laboratory. Clinical laboratory in a hospital setting showing several automated analysers. A medical laboratory or clinical laboratory is a laboratory where tests are conducted out on clinical specimens to obtain information about the health of a patient to aid in diagnosis, treatment, and prevention of disease. [ 1]
Ion chromatography (or ion-exchange chromatography) is a form of chromatography that separates ions and ionizable polar molecules based on their affinity to the ion exchanger. [ 1] It works on almost any kind of charged molecule —including small inorganic anions, [ 2] large proteins, [ 3] small nucleotides, [ 4] and amino acids.
Type I and type II errors. In statistical hypothesis testing, a type I error, or a false positive, is the rejection of the null hypothesis when it is actually true. For example, an innocent person may be convicted. A type II error, or a false negative, is the failure to reject a null hypothesis that is actually false.
Immunoassay. An immunoassay ( IA) is a biochemical test that measures the presence or concentration of a macromolecule or a small molecule in a solution through the use of an antibody (usually) or an antigen (sometimes). The molecule detected by the immunoassay is often referred to as an "analyte" and is in many cases a protein, although it may ...
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