Introduction
The measures which condense the huge mass of data into a single value representing all of theth and around which most of the data tend to concentrate are known as averages. Measure of such single value is known as measure of central tendency.
Of the various measures of central tendency, we deal here briefly only those which are frequently used in the subsequent chapters. The measures of dispersion helps to interpret the variability of data. It means we will be able to know how much homogenous or heterogeneous the data is. There are two types of dispersion which are Absolute Measure and Relative Measure of Dispersion.
Absolute and Relative Measures
Those measures of dispersion whose units are same as the units of the given series are known as the absolute measure of dispersion. These types of dispersions can be used only comparing the variability of the series (or distribution) having the same units. Comparison of two distributions with different units can not be made with absolute measures.
On the otherhand, the relative measures of dispersions are obtained as the ratio of absolute measure of dispersion to suitable average and are thus a pure number independent of units. Hence t distributions with different units can be compared with the help of relative measures of dispersion.
Methods of measuring dispersion
The following are the methods of measuring dispersion.
i. Range
ii. Semi interquartile range or Quartile deviation
iii. Mean deviation or Average deviation
iv. Standard deviation
Requisites of a good measure of dispersion
The good measure of dispersion must have the following characteristics:
1. The measure should be rigidly defined.
2. The measure should be simple to understand and easy to calculate.
3. All items must be included in the measure.
4. The measure must be suitable for further mathematical treatment.
5. Fluctuation of sampling in the measure should be least.
6. Extreme values should not unduly affect the measure.
