Various Uses & 4 Measures of Dispersion in Research Methodology 

Various Uses & 4 Measures of Dispersion in Research Methodology

Measure of dispersion explains the extent of variability. Dispersion helps to understand the disparity or distribution in a dataset. It gives us an idea about the variation and central valueof a unit. Range, interquartile range, standard deviation and mean deviation are the commonly used measures of dispersion. Dispersion can be calculated and measured using these methods.

Various Uses of Dispersion 

The uses of dispersion are:

i. It can be used in various fields fields such as mathematics, economics, business and finance. 

ii. Useful in making predictions for future occasions. 

iii. Helps investors in understanding the potential risks before making an investment. 

iv. It gives a clear view of the data distribution. 

v. Provides an idea about variation and middle value of a single unit. 

vi. Gives an idea about the difference in numbers from one another and the centre value. 

4 Measures of Dispersion in Research Methodology

The four measures of dispersion are 


The difference between the highest and lowest score in a dataset is range. It is an easy method of calculation. It does not use all the observations in a data distribution. So this is useful in finding only minimum and maximum values of a dataset.

Quartile Deviation:

The difference between the 25th and 75th percentile or the third quartile and the first quartile is Quartile deviation. It is the Semi-interquartile range of a dataset.

Mean Deviation or Average Deviation:

The average or mean of the deviations of the value from central tendency is called mean deviation. The central tendency can either be measurement of mean, median or mode. Average deviation or mean deviation removes the deficiencies of Range and Quartile methods. 

Standard Deviation:

Standard deviation is the most common and frequently used measure of dispersion. It is the square root of the sum average of the squared deviation measured from the mean.

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