Median – Definition With Examples
7 minutes read
Created: January 1, 2024
Last updated: January 10, 2024
The concept of the median is a fundamental one in the world of mathematics, especially in statistics and data analysis. It provides a clear understanding of the middle value in a dataset, offering a different perspective than the mean or average. Grasping the median’s concept and application is crucial for anyone delving into the basics of statistical analysis or just seeking to understand how to describe a set of numbers effectively.
What Is a Median?
A median is a value that sits in the middle of a set of numbers. It is the point that divides a list of numbers into two equal halves. Understanding medians is crucial in math because it helps us find the center of a data set. For example, if we have a series of numbers like 3, 5, 7, 9, and 11, the median is 7 because it’s the middle number.
Medians are particularly useful in understanding trends and central tendencies in a dataset. Unlike the average, or mean, which can be skewed by very high or very low numbers, the median gives a more accurate view of the data’s center. This makes it an essential tool in fields like statistics, economics, and data analysis.
Definition of a Median in Mathematics
In mathematical terms, a median is a value separating the higher half from the lower half of a data set. To find the median, you first need to arrange the numbers in ascending order. If the number of values in your dataset is odd, the median will be the middle number. However, if the dataset contains an even number of values, the median is calculated as the average of the two middle numbers.
For instance, if we have a set of numbers 2, 3, 4, 5, and 6, the median is 4. But if we have 2, 3, 4, 5, 6, and 7, the median is the average of 4 and 5, which is 4.5. This calculation ensures that exactly half of the data values are below the median and half are above.
Properties of a Median
The median has several important properties that make it a valuable tool in mathematics:

Nonsensitivity to Extremes: The median is not affected by extremely high or low values. This means it gives a more accurate reflection of the data’s central tendency, especially when there are outliers.

Uniqueness: Every set of numbers has one median. This unique value represents the middle of the dataset.

Applicability: It can be used for both numerical and ordinal data (data that can be put in order), making it versatile in different contexts.
These properties highlight the reliability and usefulness of the median in various mathematical and realworld applications.
Properties of a Median in a Number Series
When dealing with a series of numbers, the median has specific characteristics:

Divides the Series: The median splits the series into two halves. In each half, there are an equal number of data points, or the number differs by just one.

Independence from Range: The median doesn’t change if the range of the dataset changes, as long as the order of numbers and their position relative to the center remains the same.

Stability: In a progressive series, adding or removing values from the ends of the series (as long as they are not the median) does not affect the median’s value.
Difference Between Mean and Median
When comparing the mean and median, it’s essential to understand their distinct characteristics and how they each represent a data set:
Mean:
 Calculation: Add all the numbers in the set and divide by the count of numbers. For example, in the set 2, 3, 4, the mean is (2+3+4)/3 = 3.
 Sensitivity to Extremes: The mean is affected by extremely high or low values, which can skew the result.
 Best Used When: Ideal for data sets without outliers and when every value is significant.
Median:
 Calculation: The middle value in an ordered set. For an odd count of numbers, it’s the central number; for an even count, it’s the average of the two middle numbers. For instance, in the set 2, 3, 4, 5, the median is (3+4)/2 = 3.5.
 Resistance to Extremes: The median is not influenced by outliers, providing a more accurate reflection of the data’s center.
 Best Used When: Perfect for data sets with outliers or a skewed distribution.
Key Differences:
 Representation: The mean gives the arithmetic average, while the median provides the central value.
 Impact of Outliers: Outliers significantly affect the mean but have little to no impact on the median.
 Data Types: The mean is typically used for continuous data, while the median can be used for both continuous and ordinal data.
Calculating the Median
To calculate the median, follow these steps:
 Arrange the Numbers: Put the numbers in ascending order.
 Count the Numbers: Find out how many numbers there are in total.
 Find the Middle: If there’s an odd number of values, the median is the middle one. If there’s an even number, the median is the average of the two middle numbers.
For example, in the set 1, 2, 3, 4, 5, the median is 3. In the set 1, 2, 3, 4, 5, 6, the median is (3+4)/2 = 3.5.
Practice Problems on Finding the Median
 Find the median of the set 12, 15, 10, 14, 13.
 What is the median of the numbers 8, 22, 17, 9, 14, 20?
Solving these problems will help solidify your understanding of how to find medians in different scenarios.
Frequently Asked Questions on Medians
Can a median be a number not in the dataset?
Yes, in sets with an even number of values, the median can be a value that is not a part of the original dataset.
How does the median change if more data is added?
The median might change depending on where the new data is added in relation to the current median.
Is the median always a whole number?
No, in cases with an even number of values, the median can be a decimal.
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