# What Are The Measures Of Dispersion?

It is quite possible that two or more sets of data may have the same average and yet may differ from each other in other respects. Therefore, measures of central tendency are not sufficient to describe the all characteristic of the data or distribution.
Dispersion is the variation or scatterness of individual values from their central values such as mean, median and mode. In addition, the methods, which are used to measure this variation in numerical term, are called measures of dispersion or measures of variability. There are two types of measures of dispersion.

1. Absolute measures of dispersion.
2. Relative measure of dispersion.
The dispersion in terms of the same units as the unit of the data. For example if the units of the data are in cm, liter or kg the unit of measures of dispersion is also in cm, liter or kg. Absolute dispersion cannot be used to compare the variation in two or more than two sets of data. The commonly used absolute dispersion is range, quartiles, mean deviation, standard deviation, and variance.

A measures of dispersion when expressed as pure number in the form of a coefficient, percentage or ratio is called relative measures of dispersion. These measures are independent of unit of measurement, therefore can be used to compare the variation between two or more then two sets of data. The relative measures of dispersion are coefficient of range, coefficient of quartile deviation, mean coefficient of dispersion, coefficient of variation.
thanked the writer.
In my opinion the measures of dispersion are values that shows us the degree of Standard. There are two types of measures of variation.
1. Absolute measure - to show how much values vary from the central tendency.
2. Relative measures - to compare the degree of Standard between two distributions.
You can concider the following absolute measures of dispersion. Range, Inter-quartile range and quartile deviation,mean deviation, Standard deviation and variance. For each of these measures you can find the coresponding relative measures.
thanked the writer.