**Measure of Dispersion**

The dispersion is the measure of variations in the values of the variable. It measures the degree of scatteredness of the observation in a distribution around the central value.

**Range**

The measure of dispersion which is easiest to understand and easiest to calculate is the range.

Range is defined as the difference between two extreme observation of the distribution.

Range of distribution = Largest observation – Smallest observation.

**Mean Deviation**

Mean deviation for ungrouped data

For n observations x_{1}, x_{2}, x_{3},…, x_{n}, the mean deviation about their mean is given by

Mean deviation about their median M is given by

Mean deviation for discrete frequency distribution

Let the given data consist of discrete observations x_{1}, x_{2}, x_{3},……., x_{n} occurring with frequencies f_{1}, f_{2}, f_{3},……., f_{n} respectively in case

Mean deviation about their Median M is given by

Mean deviation for continuous frequency distribution

where x_{i} are the mid-points of the classes, and M are respectively, the mean and median of the distribution.

**Variance**

Variance is the arithmetic mean of the square of the deviation about mean .

Let x_{1}, x_{2}, ……x_{n} be n observations with as the mean, then the variance denoted by σ^{2}, is given by

**Standard deviation**

If σ^{2} is the variance, then σ is called the standard deviation is given by

Standard deviation of a discrete frequency distribution is given by

Standard deviation of a continuous frequency distribution is given by

**Coefficient of Variation**

In order to compare two or more frequency distributions, we compare their coefficient of variations. The coefficient of variation is defined as

Note: The distribution having a greater coefficient of variation has more variability around the central value, then the distribution having a smaller value of the coefficient 0f variation.