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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]
Blood compatibility testing is routinely performed before a blood transfusion. The full compatibility testing process involves ABO and RhD (Rh factor) typing; screening for antibodies against other blood group systems; and crossmatching, which involves testing the recipient's blood plasma against the donor's red blood cells as a final check for ...
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 ...
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 ...
The range in amount of possible random errors is sometimes referred to as the precision. Random errors may arise because of the design of the instrument. In particular they may be subdivided between errors in the amount shown on the display, and; how accurately the display can actually be read.
Sensitivity (true positive rate) is the probability of a positive test result, conditioned on the individual truly being positive. Specificity (true negative rate) is the probability of a negative test result, conditioned on the individual truly being negative. If the true status of the condition cannot be known, sensitivity and specificity can ...
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. For example: a guilty person may be not convicted.
Scientific misconduct is the violation of the standard codes of scholarly conduct and ethical behavior in the publication of professional scientific research. It is violation of scientific integrity: violation of the scientific method and of research ethics in science, including in the design, conduct, and reporting of research.
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