Observations within a data set are not of equal value; they vary along a given scale. The extent to which they vary between and among themselves can be indicated by measures of variation or variability. Measures of variability show the amount of dispersion in the data set or, in other words, how much the observations or values are spread out along the scale. Dispersion within a data set can be measured or described in several ways, including the range, interquartile range, and standard deviation. This entry provides a definition, description, and calculation of each measure of variability along with advantages and disadvantages in using each. It also includes a discussion of standard deviation in a normal distribution, or the empirical rule, and Chebyshev’s theorem.
Measures of ...
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