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  2. Variability - Wikipedia

    en.wikipedia.org/wiki/Variability

    Genetic variability, a measure of the tendency of individual genotypes in a population to vary from one another; Heart rate variability, a physiological phenomenon where the time interval between heart beats varies; Human variability, the range of possible values for any measurable characteristic, physical or mental, of human beings

  3. Statistical dispersion - Wikipedia

    en.wikipedia.org/wiki/Statistical_dispersion

    In statistics, dispersion (also called variability, scatter, or spread) is the extent to which a distribution is stretched or squeezed. [1] Common examples of measures of statistical dispersion are the variance, standard deviation, and interquartile range. For instance, when the variance of data in a set is large, the data is widely scattered.

  4. Biodiversity - Wikipedia

    en.wikipedia.org/wiki/Biodiversity

    Biodiversity is the variability of life on Earth. It can be measured on various levels. There is for example genetic variability, species diversity, ecosystem diversity and phylogenetic diversity. [1] Diversity is not distributed evenly on Earth.

  5. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    When there are two independent causes of variability capable of producing in an otherwise uniform population distributions with standard deviations and , it is found that the distribution, when both causes act together, has a standard deviation +. It is therefore desirable in analysing the causes of variability to deal with the square of the ...

  6. Dependent and independent variables - Wikipedia

    en.wikipedia.org/wiki/Dependent_and_independent...

    The term e i is known as the "error" and contains the variability of the dependent variable not explained by the independent variable. [citation needed] With multiple independent variables, the model is y i = a + bx i,1 + bx i,2 + ... + bx i,n + e i, where n is the number of independent variables. [citation needed]

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  8. Errors and residuals - Wikipedia

    en.wikipedia.org/wiki/Errors_and_residuals

    Thus to compare residuals at different inputs, one needs to adjust the residuals by the expected variability of residuals, which is called studentizing. This is particularly important in the case of detecting outliers, where the case in question is somehow different from the others in a dataset. For example, a large residual may be expected in ...

  9. AOL Mail - AOL Help

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    Get answers to your AOL Mail, login, Desktop Gold, AOL app, password and subscription questions. Find the support options to contact customer care by email, chat, or phone number.