General. (a) Any discrepancy between a computed, observed, or measured quantity and the true, specified, or theoretically correct value of that quantity. (1) Random Error: In statistics, an error that can be predicted only on a statistical basis; (2) Systematic Error: In statistics, an error which results from some bias in the measurement process and is not due to chance, in contrast to random error. [AIHA, 2000: Risk Assessment Principles for the Industrial Hygienist]; (b) (1) A false or mistaken result obtained in a study or experiment. Several kinds of error can occur in epidemiology, for example, due to bias. (2) Random Error (Sampling Error) is that due to chance, when the result obtained in the sample differs from the result that would be obtained if the entire population ("universe") were studied. Two varieties of sampling error are type I, or alpha error, and type II, or beta error. In an experiment, if the experimental procedure does not in reality have any effect, an apparent difference between experimental and control groups may nevertheless be observed by chance, a phenomenon known as type I error. Another possibility is that the treatment is effective but by chance the difference is not detected on statistical analysis-type II error. In the theory of testing hypotheses, rejecting a null hypothesis when it is actually true is called "type I error." Accepting a null hypothesis when it is incorrect is called "type II error." (3) Systematic Error is that due to factors other than chance, such as faulty measuring instruments. It is further considered in bias. [Last, 1983: A Dictionary of Epidemiology]