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  2. Bias (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bias_(statistics)

    Detection bias occurs when a phenomenon is more likely to be observed for a particular set of study subjects. For instance, the syndemic involving obesity and diabetes may mean doctors are more likely to look for diabetes in obese patients than in thinner patients, leading to an inflation in diabetes among obese patients because of skewed detection efforts.

  3. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    where ¯ is the sample mean, s is the sample standard deviation, m 2 is the (biased) sample second central moment, and m 3 is the (biased) sample third central moment. [6] is a method of moments estimator. Another common definition of the sample skewness is [6] [7]

  4. Sampling bias - Wikipedia

    en.wikipedia.org/wiki/Sampling_bias

    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 ...

  5. Bias of an estimator - Wikipedia

    en.wikipedia.org/wiki/Bias_of_an_estimator

    The sample mean, on the other hand, is an unbiased [5] estimator of the population mean μ. [3] Note that the usual definition of sample variance is = = (¯), and this is an unbiased estimator of the population variance.

  6. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    Bias: The bootstrap distribution and the sample may disagree systematically, in which case bias may occur. If the bootstrap distribution of an estimator is symmetric, then percentile confidence-interval are often used; such intervals are appropriate especially for median-unbiased estimators of minimum risk (with respect to an absolute loss ...

  7. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    The selective effect of cellular telephones on data collection (discussed in the Overgeneralization section) is one potential example; If young people with traditional telephones are not representative, the sample can be biased. Sample surveys have many pitfalls and require great care in execution. [18]

  8. List of cognitive biases - Wikipedia

    en.wikipedia.org/wiki/List_of_cognitive_biases

    Egocentric bias is the tendency to rely too heavily on one's own perspective and/or have a different perception of oneself relative to others. [35] The following are forms of egocentric bias: Bias blind spot, the tendency to see oneself as less biased than other people, or to be able to identify more cognitive biases in others than in oneself. [36]

  9. Unbiased estimation of standard deviation - Wikipedia

    en.wikipedia.org/wiki/Unbiased_estimation_of...

    Correction factor versus sample size n.. When the random variable is normally distributed, a minor correction exists to eliminate the bias.To derive the correction, note that for normally distributed X, Cochran's theorem implies that () / has a chi square distribution with degrees of freedom and thus its square root, / has a chi distribution with degrees of freedom.