Difference Between Mean and Median Explained

Difference Between Mean and Median Explained

In statistics, two of the most commonly used measures of central tendency are mean and median. Many students get confused between mean and median because both represent the “average” of a dataset. However, they are calculated differently and are used in different situations. Let us understand the difference between mean and median explained in a simple and clear way.


What is Mean?

The mean is generally known as the average. It is calculated by adding all the values in a dataset and dividing the total by the number of values.

Formula for Mean:



Example:

Find the mean of the following numbers.

4, 7, 3, 5, 1

Solution:

Step 1: Add the numbers.
4 + 7 + 3 + 5 + 1 = 20

Step 2: Divide the sum by total numbers (5).
20 ÷ 5 = 4

So, the mean is 4.

The concept of mean is widely used in mathematics and statistics and is strongly connected with the ideas developed in probability theory.


What Is Median?

The median is the middle value in a dataset when the numbers are arranged in ascending (smallest to largest) or descending (largest to smallest) order.

Steps to Find Median:

1.     Arrange numbers in order.

2.     Find the middle number.

If there is:

  • Odd number of values → The middle value is the median.
  • Even number of values → Take the average of the two middle numbers.

Example 1 (Odd Number of Values):

Numbers: 2, 5, 8, 10, 13

The middle number is 8.
So, median = 8

Example 2 (Even Number of Values):

Numbers: 3, 6, 7, 9, 12, 15

The middle numbers are 7 and 9.

Average = (7 + 9) ÷ 2 = 8

So, median = 8


Key Differences Between Mean and Median

Mean

Median

Sum of values ÷ total number

Middle value in ordered data

Affected by extreme values (outliers)

Not affected much by extreme values

Used in symmetric data

Used in skewed data


Effect of Outliers

An important difference appears when extreme values are present.

Example:
2, 3, 4, 5, 100

Mean = (2 + 3 + 4 + 6 + 100) ÷ 5 = 115 ÷ 5 = 23
Median = 4

Here, the mean is heavily influenced by 100, but the median is not affected. That is why median is preferred when data has very high or very low values.


When to Use Mean?

  • Test match scores
  • Scientific calculations
  • Financial averages
  • When data is evenly distributed

When to Use Median?

  • Income data
  • Real estate prices
  • Skewed distributions
  • When outliers exist

Conclusion

The mean gives the overall average by using all values in the dataset, while the median gives the middle value after rearranging the data in order. The mean is sensitive to extreme numbers, but the median is more stable in such cases.

Understanding the difference between mean and median helps in analysing data correctly and choosing the right measure depending on the situation.

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