CONCEPT OF CENTRAL TENDENCY

For a proper appreciation of various statistical measures used in analysing a frequency distribution, it is necessary to note that most of the statistical distributions have some common features. If we move from lowest value to the highest value of a variable, the number of items at each successive stage increases till we reach a maximum value, and then as we proceed further they decrease. The statistical data which follow this general pattern may differ from one variable to another in the following three ways:




1) They may differ in the values of the valuables around which most of the items cluster (i.e., Average)

2) They may differ in the extent to which items are dispersed (i.e., Dispersion).

3) They may differ in the extent of departure from some standard distributions called normal distribution (i.e., Skewness and Kurtosis).

 

Accordingly, there are three sets of statistical measures to study these three kinds of characteristics. Let us discuss the first set of measures which are called Averages or Measures of Central Tendency or Measures of Location. We discuss about the other set of measure (i.e., measures of dispersion) in next unit of this Block. In the general pattern of distribution, in the data we may identify a value around which many other items of the data congregate. This is a value which is somewhere in the central part of the range of all values. When this typical item of the data is towards the central part of the data, it is known as Central Tendency.

 

Let us see some definitions of central tendency: 

Clark defined it as “Average is an attempt to find one single figure to describe whole of figures”.  Croxtan and Cowden defined as “An average value is a single value within the range of the data that is used to represent all of the values in the series.  Since an average is somewhere within the range of the data, it is something called a measure of central value.” 

 

The above definitions explain us that the average or central value is a single value which represents the entire complex mass of data.  Therefore, central value lies somewhere in between the highest value and the lowest value of the given data.  Thus an average of a given data is frequently referred to as a measure of central tendency.

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