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Measures of dispersion give an estimate and express quantitatively the deviation of individual scores in a given sample from the mean and median. Thus, the numerical measures of variability spread or scatter around a central value. In measuring dispersion, it is imperative to know the amount of variation
The absolute measures of dispersion are used to measure the variability of a given data expressed in the same unit, while the relative measures are used to compare the variability of two or more sets of observations.
Our measure of spread will be the average squared deviation of values from the sample mean. This is called the sample variance. One Measure of Spread
Dispersion (a.k.a., variability, scatter, or spread)) characterizes how stretched or squeezed of the data. A measure of statistical dispersion is a nonnegative real number that is zero if all the data are the same and increases as the data become more diverse. Dispersion is contrasted with location or central tendency, and
measure of dispersion is its sensitivity to changes in extreme values. One measure of dispersion which avoids this difficulty is the interquartile range. This is defined as the difference between the first and third quartile values, that is: Interquartile range Measures of Dispersion 51
of data. In this chapter, we will discuss some statistical techniques used to measure dispersion, that is the range, quartiles, variance, standard deviation, coefficient of variation and coefficient of skewness. The online version of this chapter (doi:10.1007/978-3-319-26497-4_4) contains supplementary material, which is available to ...
A measure of dispersion provides a summary statistic that indicates the magnitude of such dispersion and, like a measure of central tendency, is a univariate statistic. Importance of the Magnitude Dispersion Around the Average. Dispersion around the mean test score.
