📊 Mean, Median & Mode Calculator
Drop in a list of numbers — separated by commas, spaces, or new lines — and get the mean, median, and mode plus count, sum, min, max, and range in one pass.
📊 Summarise Any Data Set
What is a Mean, Median & Mode Calculator?
It computes the three classic measures of central tendency for a data set at once. The mean is the average, the median is the middle value, and the mode is the most frequent value — each answers "what is a typical value here?" from a slightly different angle, and reading them together tells you far more than any one alone.
Use it to summarise survey responses, sensor readings, test scores, or any column of numbers before you model or chart them. When the mean and median pull apart, your data is skewed; when several values tie for the mode, the distribution may be multimodal. Treat these as a first look — always eyeball the raw distribution too.
❓ Frequently Asked Questions
What is the difference between mean, median, and mode?
The mean is the arithmetic average — the sum of all values divided by how many there are. The median is the middle value when the data is sorted (or the average of the two middle values for an even count). The mode is the value that appears most often. Together they describe where your data centres, and comparing them reveals skew.
How is the median calculated for an even number of values?
The list is sorted and the two middle values are averaged. For example, in {1, 2, 3, 4} the two central values are 2 and 3, so the median is 2.5. For an odd count, the single middle value is taken directly.
What happens when there are ties for the mode?
When two or more values share the highest frequency, this calculator reports the smallest of the tied values so the result is deterministic. Some data sets are genuinely multimodal — in that case, inspect the full distribution rather than relying on a single mode.
When should I use the median instead of the mean?
Prefer the median when your data is skewed or contains outliers, because a few extreme values can drag the mean away from the bulk of the data. Income and house prices are classic cases where the median is more representative than the mean.