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  2. Coefficient of variation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_variation

    The data set [90, 100, 110] has more variability. Its standard deviation is 10 and its average is 100, giving the coefficient of variation as 10 / 100 = 0.1; The data set [1, 5, 6, 8, 10, 40, 65, 88] has still more variability. Its standard deviation is 32.9 and its average is 27.9, giving a coefficient of variation of 32.9 / 27.9 = 1.18

  3. 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.

  4. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    This term was intended to be analogous to the coefficient of variation, for describing multiplicative variation in log-normal data, but this definition of GCV has no theoretical basis as an estimate of itself (see also Coefficient of variation). Note that the geometric mean is smaller than the arithmetic mean.

  5. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    Consider the linear regression equation = +, =, …,, where the dependent random variable equals the deterministic variable times coefficient plus a random disturbance term that has mean zero. The disturbances are homoscedastic if the variance of ε i {\displaystyle \varepsilon _{i}} is a constant σ 2 {\displaystyle \sigma ^{2}} ; otherwise ...

  6. McKay's approximation for the coefficient of variation

    en.wikipedia.org/wiki/McKay's_approximation_for...

    In statistics, McKay's approximation of the coefficient of variation is a statistic based on a sample from a normally distributed population. It was introduced in 1932 by A. T. McKay. [1] Statistical methods for the coefficient of variation often utilizes McKay's approximation. [2] [3] [4] [5]

  7. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).

  8. Index of dispersion - Wikipedia

    en.wikipedia.org/wiki/Index_of_dispersion

    In probability theory and statistics, the index of dispersion, [1] dispersion index, coefficient of dispersion, relative variance, or variance-to-mean ratio (VMR), like the coefficient of variation, is a normalized measure of the dispersion of a probability distribution: it is a measure used to quantify whether a set of observed occurrences are clustered or dispersed compared to a standard ...

  9. Bivariate analysis - Wikipedia

    en.wikipedia.org/wiki/Bivariate_analysis

    Regression is a statistical technique used to help investigate how variation in one or more variables predicts or explains variation in another variable. Bivariate regression aims to identify the equation representing the optimal line that defines the relationship between two variables based on a particular data set.