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<p align="justify">Characteristic of data which describes the extent to which the observations vary among themselves is called dispersion. In other words it is the scatter or spread of the values from one another or from some common value. It is important to calculate the dispersions because averages do not give the clear picture of the data. They lack the information of how much observations are deviated or scattered from their central value or how much they tend toward their central value. For example if we state that two batsmen A and B made average score of 45 runs for the last 60 matches. Now due to difference in dispersion from the average score one cannot conclude that the two batsmen got the identical score in every match. If the same statement is expressed such as, Batsman A made the average score of 45 runs with the average dispersion of 20 runs and Batsman B made the average score of 45 runs with the average dispersion of 10 runs. It shows a close picture of the runs of the two batsmen. All those methods which are used to measure the amount of dispersion present in any data are called measures of dispersion or measures of variation.&#160; </p>
<p align="justify">Measures of Dispersion are:</p>
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<div align="justify"><a href="http://mba-lectures.com/statistics/descriptive-statistics/279-range.html" target="_blank" rel="noopener">Range</a></div>
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<div align="justify"><a href="http://mba-lectures.com/statistics/descriptive-statistics/302-quartile-deviation-or-semi-interquartile-range-grouped-data.html" target="_blank" rel="noopener">Quartile deviation or Semi-interquartile Range</a></div>
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<div align="justify"><a href="http://mba-lectures.com/statistics/descriptive-statistics/338-mean-absolute-deviation.html" target="_blank" rel="noopener">Mean absolute deviation</a></div>
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<div align="justify"><a href="http://mba-lectures.com/statistics/descriptive-statistics/349-standard-deviation.html" target="_blank" rel="noopener">Standard deviation</a> </div>
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