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One of the best-known examples of Simpson's paradox comes from a study of gender bias among graduate school admissions to University of California, Berkeley.The admission figures for the fall of 1973 showed that men applying were more likely than women to be admitted, and the difference was so large that it was unlikely to be due to chance.
The request to sign a petition was made two weeks prior to the request to make a donation. They found that a greater percentage of people made a donation in the foot-in-the-door condition than in the control condition. Also, they found that making the small request to sign a petition resulted in more money being donated than not making this ...
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. [2]
Graphs of probabilities of getting the best candidate (red circles) from n applications, and k/n (blue crosses) where k is the sample size. The secretary problem demonstrates a scenario involving optimal stopping theory [1] [2] that is studied extensively in the fields of applied probability, statistics, and decision theory.
Example: We visit every household in a given street, and interview the first person to answer the door. In any household with more than one occupant, this is a nonprobability sample, because some people are more likely to answer the door (e.g. an unemployed person who spends most of their time at home is more likely to answer than an employed ...
Research dating back to Émile Durkheim suggests that predominantly Protestant localities have higher suicide rates than predominantly Catholic localities. [3] According to Freedman, [4] the idea that Durkheim's findings link, at an individual level, a person's religion to their suicide risk is an example of the ecological fallacy.
[1] [2] The persuader attempts to convince the respondent to comply by making a large request that the respondent will most likely turn down, much like a metaphorical slamming of a door in the respondent's face. The respondent is then more likely to agree to a second, more reasonable request, than if that same request is made in isolation.
Table 1: Kent's "words of estimative probability" [2] Certain 100% Give or take 0% The general area of possibility: Almost certain 93% Give or take about 6% Probable 75% Give or take about 12% Chances about even 50% Give or take about 10% Probably not 30% Give or take about 10% Almost certainly not 7% Give or take about 5% Impossible 0 Give or ...