Mean, Median & Mode Calculator

Enter your dataset below to instantly calculate all three measures of central tendency — with complete step-by-step workings, formulas, and explanations.

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Enter Your Data

Dataset (comma or space separated) You can separate numbers with commas, spaces, or new lines.

Understanding Mean, Median, and Mode

The Mean (Arithmetic Average)

The mean is the most common measure of central tendency. You find it by adding all values together and then dividing by the count of values.

Mean = (x₁ + x₂ + x₃ + … + xₙ) / n

Example: For the dataset 3, 7, 5, 9, 1:

Mean = (3 + 7 + 5 + 9 + 1) / 5 = 25 / 5 = 5

When the mean can be misleading: The mean is sensitive to extreme values (outliers). For example, if most students scored 50–60 on a test but one student scored 0, the mean would be pulled downward and not represent the typical score well.

The Median (Middle Value)

The median is the middle value when data is arranged in order. It is not affected by outliers, making it a better measure for skewed data.

For an odd number of values: The median is the middle item.

For an even number of values: The median is the average of the two middle items.

Position of median = (n + 1) / 2 [for odd n]

Example (odd): Data: 2, 5, 7, 8, 11 → Median = 7

Example (even): Data: 2, 5, 7, 8 → Median = (5 + 7) / 2 = 6

The Mode (Most Frequent Value)

The mode is the value that appears most often in a dataset. A dataset can have no mode, one mode (unimodal), two modes (bimodal), or many modes (multimodal).

Example: In the dataset 3, 5, 3, 7, 3, 8, 5, the value 3 appears 3 times — more than any other value. Mode = 3.

No mode: If all values appear equally often (e.g. 1, 2, 3, 4), there is no mode.

The mode is especially useful for: Categorical data (e.g. most popular shirt size), finding the most common test score, or analyzing survey results.

When to Use Which Average?

Situation	Best Measure	Reason
No extreme values, numerical data	Mean	Uses all data values
Skewed data or outliers present	Median	Not affected by extremes
Categorical data or "most common"	Mode	Works for non-numerical data
Income data (usually skewed)	Median	Resists effect of very high earners
Test scores (roughly symmetric)	Mean	Most informative summary
Shoe/clothing sizes for stock	Mode	Most frequently needed size

Quick Examples

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How to Use

Enter numbers separated by commas or spaces.
Click Calculate to get results.
Read the step-by-step solution below.
Use the copy button to copy any result.

Frequently Asked Questions

A dataset can be bimodal (two modes) or multimodal (more than two modes). The calculator will display all mode values. For example, in the dataset 2, 3, 3, 5, 5, 7, both 3 and 5 are modes.

When data is symmetric (bell-shaped), mean ≈ median. When data is skewed — for example, a few very large values pulling the distribution to the right — the mean is higher than the median. This is called positive (right) skew. The median is more robust because it is not affected by extreme values.

There is no hard limit. You can enter hundreds or thousands of values. For very large datasets, consider using the CSV to Table tool first to organize your data.