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Measures of Dispersion
- The measures of dispersion are extremely useful in statistical work since they indicate whether the rest of the data are scattered away from the mean or around the mean.
- If the data is roughly dispersed around the mean so the measure of dispersion acquired will be small hence indicating that the mean is an excellent representative of the sample data. However on the other hand, if the figures are not closely located to the mean then the measures of dispersion acquired will be relatively big indicating that the mean does not present the data sufficiently
- The generally used measures of dispersion are as
a) The range
- The range is explained as the difference between the smallest and the highest values in a frequency distribution. This measure is not extremely efficient since it utilizes only two values in a described frequency distribution. Conversely the smaller the value of the range, the less dispersed the observations are from the arithmetic mean (a.m.) and vice versa
- The range is not generally used in business management since two sets of data may yield the similar range but end up containing different interpretations regarding the degree of dispersion
b) The absolute mean deviation
- It is useful measures of dispersion since it makes use of all the values described see the given illustration;
The Fisher's index The index of Fisher acts as a compromise between Paasche' index and Laspeyre's index. This is calculated as a geometric mean of the two indexes.
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