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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
a measure of location, or central tendency, such as the arithmetic mean; a measure of statistical dispersion like the standard mean absolute deviation; a measure of the shape of the distribution like skewness or kurtosis; if more than one variable is measured, a measure of statistical dependence such as a correlation coefficient
Coefficient of variation: Normalizing dispersion, using the mean as a measure of scale, particularly for positive distribution such as the exponential distribution and Poisson distribution. Min-max feature scaling
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]
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 ...
In estimating the mean of uncorrelated, identically distributed variables we can take advantage of the fact that the variance of the sum is the sum of the variances.In this case efficiency can be defined as the square of the coefficient of variation, i.e., [13]
McKay's approximation for the coefficient of variation; Mean absolute difference; Mean absolute error; Mean absolute percentage error; Mean absolute scaled error; Mean square quantization error; Mean squared displacement; Mean squared error; Mean squared prediction error; Medcouple; Median absolute deviation; Minimum mean square error; MINQUE
a diameter which indicates the median; a fan (a segment of a circle) which indicates the quartiles; two feathers which indicate the extreme values. The scale on the circular line begins at the left with the starting value (e. g. with zero). The following values are applicated clockwise. The white tail of diameter indicates the median.