Measures of central tendency are very useful in Statistics. Their importance is because of the following reasons:

(i) To find representative value:

Measures of central tendency or averages give us one value for the distribution and this value represents the entire distribution. In this way averages convert a group of figures into one value.

(ii) To condense data:


Collected and classified figures are vast. To condense these figures we use average. Average converts the whole set of figures into just one figure and thus helps in condensation.

(iii) To make comparisons:

To make comparisons of two or more than two distributions, we have to find the representative values of these distributions. These representative values are found with the help of measures of the central tendency.

(iv) Helpful in further statistical analysis:


Many techniques of statistical analysis like Measures of Dispersion, Measures of Skewness, Measures of Correlation, and Index Numbers are based on measures of central tendency. That is why; measures of central tendency are also called as measures of the first order.

Seeing this importance of averages in statistics, Prof. Bowley said “Statistics may rightly be called as science of averages.”