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Terms Definitions
Technological surprise
Transparency The degree to which a model is transparent. A model is said to be transparent if all key assumptions that underlie the model are accessible and understandable for the users.
Type I error also: Error of the first kind. In hypothesis testing, this error is caused by incorrect rejection of the hypothesis when it is true. Any test is at risk of being too selective and too sensitive. The design of the test, especially confidence limits, aims at reducing the likelihood of one type of error at the price of increasing the other. Thus, all such statistical tests are value laden.
Type II error also: Error of the second kind. In hypothesis testing this error is caused by not rejecting the hypothesis when it is false.
Type III error also: Error of the third kind. Assessing or solving the wrong problem by incorrectly accepting the false meta-hypothesis that there is no difference between the boundaries of a problem, as defined by the analyst, and the actual boundaries of that problem (Raifa, 1968, redefined by Dunn, 1997, 2000).
 
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