Quartile Deviation:
It is based on the lower quartile and the upper quartile . The difference is called the inter quartile range. The difference divided by is called semiinterquartile range or the quartile deviation. Thus
The quartile deviation is a slightly better measure of absolute dispersion than the range. But it ignores the observation on the tails. If we take difference samples from a population and calculate their quartile deviations, their values are quite likely to be sufficiently different. This is called sampling fluctuation. It is not a popular measure of dispersion. The quartile deviation calculated from the sample data does not help us to draw any conclusion (inference) about the quartile deviation in the population.
Coefficient of Quartile Deviation:
A relative measure of dispersion based on the quartile deviation is called the coefficient of quartile deviation. It is defined as
Coefficient of Quartile Deviation
It is pure number free of any units of measurement. It can be used for comparing the dispersion in two or more than two sets of data.
Example:
The wheat production (in Kg) of 20 acres is given as: 1120, 1240, 1320, 1040, 1080, 1200, 1440, 1360, 1680, 1730, 1785, 1342, 1960, 1880, 1755, 1720, 1600, 1470, 1750, and 1885. Find the quartile deviation and coefficient of quartile deviation.
Solution:
After arranging the observations in ascending order, we get
1040, 1080, 1120, 1200, 1240, 1320, 1342, 1360, 1440, 1470, 1600, 1680, 1720, 1730, 1750, 1755, 1785, 1880, 1885, 1960.
Example:
Calculate the quartile deviation and coefficient of quartile deviation from the data given below:
Maximum Load
(shorttons) 
Number of Cables 
















Solution:
The necessary calculations are given below:
Maximum Load
(shorttons) 
Number of Cables 
Class 
Cumulative 
































lies in the class
Where , , , and
lies in the class
Where , , , and