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Overconfidence effect, a tendency to have excessive confidence in one's own answers to questions. For example, for certain types of questions, answers that people rate as "99% certain" turn out to be wrong 40% of the time. [5] [44] [45] [46] Planning fallacy, the tendency for people to underestimate the time it will take them to complete a ...
Acquiescence bias, which is also referred to as "yea-saying", is a category of response bias in which respondents to a survey have a tendency to agree with all the questions in a measure. [ 14 ] [ 15 ] This bias in responding may represent a form of dishonest reporting because the participant automatically endorses any statements, even if the ...
[3] [2] [4] Some argue that these findings indicate that test bias plays a role in producing the gaps in IQ test scores. [5] Both of these tests demonstrate how cultural content on intelligence tests may lead to culturally biased score results. Still, these criticisms of cultural content may not apply to "culture free" tests of intelligence.
A majority chose answer (b). Independent of the information given about Linda, though, the more restrictive answer (b) is under any circumstance statistically less likely than answer (a). This is an example of the "conjunction fallacy". Tversky and Kahneman argued that respondents chose (b) because it seemed more "representative" or typical of ...
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In social science research social-desirability bias is a type of response bias that is the tendency of survey respondents to answer questions in a manner that will be viewed favorably by others. [1] It can take the form of over-reporting "good behavior" or under-reporting "bad" or undesirable behavior.
Questions affected by acquiescence bias take the following format: a stimulus in the form of a statement is presented, followed by 'agree/disagree,' 'yes/no' or 'true/false' response options. [ 2 ] [ 6 ] For example, a respondent might be presented with the statement "gardening makes me feel happy," and would then be expected to select either ...
But it’s just one example of a larger problem permeating health care. Numerous formulas or “algorithms” used in medical decisions — treatment guidelines, diagnostic tests, risk calculators — adjust the answers according to race or ethnicity in a way that puts people of color at disadvantage.