__NOTOC__ Extension neglect is a type of cognitive bias that occurs when the mind tends to ignore the size of the set during an evaluation in which the size of the set is logically relevant. For instance, when reading an article about a scientific study, extension neglect occurs when the reader ignores the number of people involved in the study (sample size) and concludes the article is important because of its results . In reality, if the sample size is too small, the results of the study are suspect, because the larger the sample size the more likely any non-typical subjects' answers tend to average out . A study based on only a few people may draw very invalid conclusions because only one person has exceptionally high or low scores  , and there are not enough people there to correct this via averaging out. But often, the sample size is not prominently displayed in science articles, and the reader in this case might still believe the article's conclusion due to extension neglect (ignoring the small sample size and therefore the large possibility of a wrong conclusion. )
__NOTOC__ Extension neglect is a type of cognitive bias which occurs when the the sample size is ignored while evaluating a study in which the sample size is logically relevant. For instance, when reading an article about a scientific study, extension neglect occurs when the reader ignores the number of people involved in the study (sample size) but still makes inferences about a population based on the sample . In reality, if the sample size is too small, the results might risk errors in statistical hypothesis testing . A study based on only a few people may draw invalid conclusions because only one person has exceptionally high or low scores (outlier) , and there are not enough people there to correct this via averaging out. But often, the sample size is not prominently displayed in science articles, and the reader in this case might still believe the article's conclusion due to extension neglect .
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that
which
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mind tends to ignore the size of the set during an evaluation
the sample size is ignored while evaluating a study
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size of the set
sample size
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and concludes the article is important because of its results
but still makes inferences about a population based on the sample
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of the study are suspect, because the larger the sample size the more likely any non-typical subjects' answers tend to average out
might risk errors in statistical hypothesis testing
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very
A
(outlier)
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(ignoring the small sample size and therefore the large possibility of a wrong conclusion. )
.