Median of a List
Enter a set of numbers separated by commas to find the median. Works with any count of numbers — even or odd.
Median, Mean & Mode Together
Calculate all three measures of central tendency — median, mean, and mode — for your dataset at once, with range and count included.
Weighted Median Calculator
Find the weighted median by entering comma-separated values and their corresponding weights. Each value and weight pair must match in count.
What is the Median?
The median is the middle value in a sorted list of numbers. It divides the dataset into two equal halves. Unlike the mean (average), the median is not affected by very large or very small outliers, making it a reliable measure of central tendency for skewed data.
Step 1 — Sort the numbers: 1, 3, 4, 7, 9
Step 2 — Count: 5 values (odd)
Step 3 — Middle position: (5 + 1) / 2 = 3rd value
Median = 4
Odd vs Even Count of Numbers
How you find the median depends on whether you have an odd or even number of values in your dataset.
Dataset: 2, 5, 8, 11, 14 → Median = 8
Even count — The median is the average of the two middle values.
Dataset: 2, 5, 8, 11 → Middle values: 5 and 8
Median = (5 + 8) / 2 = 6.5
Median vs Mean vs Mode
These three measures all describe the “center” of data, but in different ways. Understanding when to use each one leads to better data interpretation.
Mean — Sum of all values divided by the count. Best for normally distributed data.
Mode — The most frequently occurring value. Best for categorical data.
Example: 2, 3, 3, 4, 100
Mean = (2+3+3+4+100) / 5 = 22.4
Median = 3
Mode = 3
What is a Weighted Median?
A weighted median assigns importance (weight) to each value. It is the value where the cumulative weight reaches or crosses 50% of the total weight. This is useful in economics, surveys, and finance where not all data points contribute equally.
Total weight = 10
Cumulative weights (sorted by value): 1, 4, 6, 10
50% of total = 5 → Cumulative first reaches 5 at value 10
Weighted Median = 10
When to Use the Median
The median is preferred over the mean in many real-world situations. Household income statistics use the median because a small number of very high earners would inflate the mean. Home prices, test scores with outliers, and any data with a skewed distribution are better described by the median.