central tendency

CENTRAL TENDENCY, Measure of central tendency.

what is central Tendencies? Also called a measure of location, is the statistical information that gives the middle or centre or average of a set of data.

They are all regarded as forms of averages.

A measure of central tendency is a statistical measure that represents the centre or typical value of a dataset.

t provides information about the average or most representative value in a set of observations. The three most common measures of central tendency are:

Mean: The mean is calculated by summing up all the values in a dataset and dividing it by the total number of observations. It is sensitive to extreme values, as it takes into account every value in the dataset.

Median: The median is the middle value in a dataset when the values are arranged in ascending or descending order.

If there is an even number of observations, the median is the average of the two middle values. The median is less affected by extreme values and is a good measure when dealing with skewed distributions.

Mode: The mode is the value or values that appear most frequently in a dataset. A dataset can have no mode (when all values are unique), one mode (unimodal), or multiple modes (multimodal).

Unlike the mean and median, the mode can be applied to both numerical and categorical data.


Collectively or naturally, the measure of location or heaviest concentration is referred to as measures of centre tendencies.

Measures of central tendencies are consistent throughout the subject research literature and study. There are many of them. But, by far the most important and frequently used are, There are five measures of central tendencies. They are:

Arithmetic mean



Geometric mean

Harmonic mean

Quadratic mean


In the simplest cases, the measure of central tendency is an average of a set of measurements, the word average being variously construed as mean, median, or other measure of location, depending on the context.

An average is a measure of the “middle” or “typical” value of a data set. In the most common case, the data set is a list of numbers.

The average of a list of numbers is a single number intended to typify the numbers in the list. If all the numbers in the list are the same, then this number should be used.

If the numbers are not the same, the average is calculated by combining the numbers from the list in a specific way and computing a single number as being the average of the list

data usefulness of the central tendency

The specific objective of the analysis refers to the purpose or goal for which the data analysis is being conducted. Different objectives may require different measures of central tendency. Here are a few examples:

Descriptive Analysis: If the objective is to describe the general characteristics of a dataset, such as summarizing the data for reporting purposes,

the mean, median, and mode can all be useful measures of central tendency. They provide information about the typical value or values in the dataset.

Comparison of Groups: When comparing different groups or populations, the mean is often used as a measure of central tendency.

It provides an average value that can be used to compare the groups. For example, if you are comparing the average income of different professions, you would calculate the mean income for each group and compare them.

Skewed Distributions: In cases where the data is skewed or contains outliers, the median is often preferred over the mean.

The median is less affected by extreme values and provides a better representation of the \”typical\” value in such situations.

This is common when dealing with income distributions, where a few extremely high earners can significantly affect the mean.

Categorical Data: When analyzing categorical data, such as survey responses or types of products purchased, the mode is a relevant measure of central tendency.

It helps identify the most common category or response in the dataset, providing insight into the majority preference or occurrence.

It\’s important to consider the specific objective of the analysis, the nature of the data, and any specific characteristics or requirements of the dataset when choosing the appropriate measure of central tendency.


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