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  2. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.

  3. Statistical dispersion - Wikipedia

    en.wikipedia.org/wiki/Statistical_dispersion

    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. On the other hand, when the variance is small, the data in the set is clustered.

  4. Variance function - Wikipedia

    en.wikipedia.org/wiki/Variance_function

    In summary, to ensure efficient inference of the regression parameters and the regression function, the heteroscedasticity must be accounted for. Variance functions quantify the relationship between the variance and the mean of the observed data and hence play a significant role in regression estimation and inference.

  5. Data structure diagram - Wikipedia

    en.wikipedia.org/wiki/Data_structure_diagram

    Data structure diagram and a data dictionary. A data structure diagram is a diagram type that is used to depict the structure of data elements in the data dictionary. The data structure diagram is a graphical alternative to the composition specifications within such data dictionary entries. [1] The data structure diagrams is a predecessor of ...

  6. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    For example, a variable measured in meters will have a variance measured in meters squared. For this reason, describing data sets via their standard deviation or root mean square deviation is often preferred over using the variance. In the dice example the standard deviation is √ 2.9 ≈ 1.7, slightly larger than the expected absolute ...

  7. Squared deviations from the mean - Wikipedia

    en.wikipedia.org/wiki/Squared_deviations_from...

    Squared deviations from the mean (SDM) result from squaring deviations.In probability theory and statistics, the definition of variance is either the expected value of the SDM (when considering a theoretical distribution) or its average value (for actual experimental data).

  8. Qualitative variation - Wikipedia

    en.wikipedia.org/wiki/Qualitative_variation

    There are several types of indices used for the analysis of nominal data. Several are standard statistics that are used elsewhere - range, standard deviation, variance, mean deviation, coefficient of variation, median absolute deviation, interquartile range and quartile deviation.

  9. Partition of sums of squares - Wikipedia

    en.wikipedia.org/wiki/Partition_of_sums_of_squares

    If the sum of squares were not normalized, its value would always be larger for the sample of 100 people than for the sample of 20 people. To scale the sum of squares, we divide it by the degrees of freedom, i.e., calculate the sum of squares per degree of freedom, or variance. Standard deviation, in turn, is the square root of the variance.