The measure of dispersion is the measure of the extent of variation or deviation of individual values from the central value. This measure of variation gives a precise idea as to the extent of representativeness of the central value.

The standard deviation is the square root of the variance. The standard deviation plays a key role in many of the statistics. On the other hand, the sum of squares is the most basic of the measures of dispersion away from the mean. It is the sum of the squared deviations of the scores of the mean (Walsh; 1990:50). The mean deviation is the mean difference of the items in a set of data from their average. It is simply an average of absolute deviations of individuals items from the central value of a series.

In a bell-shaped symmetrical distribution there is a fixed relationship between the three most commonly used measures of variation. The quartile deviation is smallest, the mean deviation next. And the standard deviation is largest in the following proportions:

__The standard deviation, the mean deviation, the sum of squares, the standard score are the co-efficient of variation are the major part of the measure of variation. Among them, the first three standard deviation, mean deviation. Sum of squares is the absolute measure of variation and standard score are co-efficient of variation is the elative measure of variation.__The standard deviation is the square root of the variance. The standard deviation plays a key role in many of the statistics. On the other hand, the sum of squares is the most basic of the measures of dispersion away from the mean. It is the sum of the squared deviations of the scores of the mean (Walsh; 1990:50). The mean deviation is the mean difference of the items in a set of data from their average. It is simply an average of absolute deviations of individuals items from the central value of a series.

In a bell-shaped symmetrical distribution there is a fixed relationship between the three most commonly used measures of variation. The quartile deviation is smallest, the mean deviation next. And the standard deviation is largest in the following proportions: