以偏概全 Sampling bias
（重定向自Sample bias）
以偏概全，是指以少数的例证或特殊的情形，强行概括整体。
以偏概全有几种常见的形式：
- 只根据部分案例推论一般性规律（偏差样本、轻率概化、轶事证据）
- 只根据部分案例的特质推论整个群体的一般性特质（合成谬误）
- 只根据部分特例否定一般性通则（逆偶例谬误）
- 只根据部分支持的证据支持一个论点（单方论证）
Sample bias
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Sampling bias 以偏概全
（重定向自Sample bias）
![Example of biased sample: as of June 2008 55% of web browsers (Internet Explorer) in use did not pass the Acid2 test. Due to the nature of the test, the sample consisted mostly of web developers.[15]](/uploads/202502/09/Acid2compliancebyusage5025.png)
In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others. It results in a biased sample, a non-random sample of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected. If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling.
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