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It is also known as relative standard deviation.Įxample: From the above example s= 18.3 and X̅=154Ĭoefficient of variation COV = s/ X̅ * (100%)= 18.3/154*100=11.9% Inter Quartile range In other words coefficient of variation is equal to the standard deviation divided by the mean and it is express in the percentage. Coefficient of variationĬoefficient of variation is the standard deviation relative to the mean. S is the standard deviation of the sample (18.3) which is used as an estimate for the population from which the sample was taken. Sample variance is denoted by s squared and is equal to the sum of squared differences between observed sample values and the sample mean, divided by the number of sample observations minus 1. Population variance, denoted by sigma squared, is equal to the sum of squared differences between the observed values and the population mean, divided by the total number of observations. Variance measures the dispersion of a set of data points around their mean value. The disadvantage of Range- completely depends upon the extreme values.The range can be used with ordinal or interval ratio variables, but cannot be used with nominal scale.Range is the difference between the maximum and the minimum value.Įxample: The age of randomly sampled audience in a theatre is 55,16,23,65,45,34,28,37,58,24.
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There are several measures of dispersion, the most common being are To indicate the level of uniformity of variables.Facilitate computations of other statistical measures.Compare two or more data sets with regard to the variability.To determine the reliability of an average.Hence, the method of dispersion helps to find the correct variation of the data.
#Name 3 measures of dispersio series#
If the means of two or more series are the same, do not consider them similar because their other characteristics (dispersion, skewness, kurtosis), may differ. Similarly, the second set of data shows more variation around the center. From the above example, though the average salary of two sets is the same ($60K), the first set of household data indicates more uniformity. In other words, more uniformity, less the degree of variation. Uniformity and degree of variation are inversely proportional. Dispersion indicates the extent of uniformity.