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In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population have a lower or higher sampling probability than others. It results in a biased sample [ 1 ] of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected ...
For example, when getting to know others, people tend to ask leading questions which seem biased towards confirming their assumptions about the person. However, this kind of confirmation bias has also been argued to be an example of social skill; a way to establish a connection with the other person. [9]
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. [1] It is sometimes referred to as the selection effect.
For example, the square root of the unbiased estimator of the population variance is not a mean-unbiased estimator of the population standard deviation: the square root of the unbiased sample variance, the corrected sample standard deviation, is biased. The bias depends both on the sampling distribution of the estimator and on the transform ...
Implicit bias is an aspect of implicit social cognition: the phenomenon that perceptions, attitudes, and stereotypes operate without conscious intention. For example, researchers may have implicit bias when designing survey questions and as a result, the questions do not produce accurate results or fail to encourage survey participation. [124]
Spectrum bias arises from evaluating diagnostic tests on biased patient samples, leading to an overestimate of the sensitivity and specificity of the test. For example, a high prevalence of disease in a study population increases positive predictive values, which will cause a bias between the prediction values and the real ones. [4]
Biases that affect memory, [18] such as consistency bias (remembering one's past attitudes and behavior as more similar to one's present attitudes). Biases that reflect a subject's motivation, [19] for example, the desire for a positive self-image leading to egocentric bias and the avoidance of unpleasant cognitive dissonance. [20]
The study considered whether the display or non-display of photographs biased subjects' estimates as to the percentage of Yale (vs Stanford) students in the sample of men and women whose names appeared on the original list, and whether these estimated percentages were causally related to the respondents' memory for the college affiliations of ...