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Regarding the selection of classification parameters, a common method is to divide the data into two sets, and find the optimum parameter using one set and then test using this parameter value on the second set. This is a standard technique [citation needed] used (for example) by the princeton MVPA classification library. [2]
The larger this ratio is, the more skew the derived-quantity PDF may be, and the more bias there may be. The Taylor-series approximations provide a very useful way to estimate both bias and variability for cases where the PDF of the derived quantity is unknown or intractable.
In cognitive science and behavioral economics, loss aversion refers to a cognitive bias in which the same situation is perceived as worse if it is framed as a loss, rather than a gain. [ 1 ] [ 2 ] It should not be confused with risk aversion , which describes the rational behavior of valuing an uncertain outcome at less than its expected value .
There are multiple other cognitive biases which involve or are types of confirmation bias: Backfire effect, a tendency to react to disconfirming evidence by strengthening one's previous beliefs. [32] Congruence bias, the tendency to test hypotheses exclusively through direct testing, instead of testing possible alternative hypotheses. [12]
The negativity bias, [1] also known as the negativity effect, is a cognitive bias that, even when positive or neutral things of equal intensity occur, things of a more negative nature (e.g. unpleasant thoughts, emotions, or social interactions; harmful/traumatic events) have a greater effect on one's psychological state and processes than neutral or positive things.
In educational measurement, bias is defined as "Systematic errors in test content, test administration, and/or scoring procedures that can cause some test takers to get either lower or higher scores than their true ability would merit." [16] The source of the bias is irrelevant to the trait the test is intended to measure.
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The implicit-association test (IAT) is an assessment intended to detect subconscious associations between mental representations of objects in memory. [1] Its best-known application is the assessment of implicit stereotypes held by test subjects, such as associations between particular racial categories and stereotypes about those groups. [2]