Mean Median Mode Calculator
Paste numbers to get the mean, median, mode, range, variance, standard deviation, quartiles, IQR and outliers — all at once. Free, runs in your browser.
Mean, Median, Mode and Spread Calculator
This tool computes descriptive statistics — they summarise the numbers you enter. They do not, on their own, support inferential conclusions about a wider population, which depend on sample size and how the data were collected.
How to Use the Statistics Calculator
Paste your numbers
Type or paste your data into the box, separated by commas, spaces, or new lines — so a column copied from a spreadsheet works directly.
Read the averages
You instantly get the three "averages" — mean, median, and mode — plus the count, sum, minimum, maximum, range, and midrange.
See the spread
Below that you get the variance and standard deviation (both sample and population), the quartiles, the interquartile range, and any outliers flagged by the 1.5×IQR rule.
Interpret carefully
Use the mean for symmetric data and the median when there are outliers. The standard deviation tells you how spread out the numbers are around the mean.
Averages and Spread, Explained
Three Different "Averages"
In everyday speech "average" means one thing, but in statistics there are three, and they can tell very different stories about the same data. The mean is the familiar one: add everything up and divide by how many numbers there are. The median is the middle value when the numbers are sorted — half are below it, half above. The mode is simply the value that occurs most often. For a tidy, symmetric set of numbers these three land close together, but the moment the data is skewed or contains an outlier they diverge, and that divergence is informative. A classic example is income: a single very high earner pulls the mean upward while leaving the median — the "typical" person — almost untouched. That is exactly why news reports about pay or house prices usually quote the median: it resists distortion by extremes. This calculator gives you all three at once, so you can see whether they agree (the data is well-behaved) or disagree (something interesting is going on).
Knowing the centre of your data is only half the picture; the other half is spread — how tightly or loosely the numbers cluster. Two classes can have the same average test score while one is uniformly mediocre and the other is split between high-flyers and strugglers. The range (max minus min) is the crudest measure of spread; the standard deviation is the workhorse, telling you the typical distance of a value from the mean. This tool reports both the sample and population versions, because the distinction matters: when your numbers are a sample drawn from a larger group, you divide by one fewer than the count (Bessel's correction) to avoid underestimating the true spread; when your numbers are the whole group, you divide by the count itself. It also gives the quartiles and the interquartile range — the spread of the middle half — and flags outliers using the standard 1.5×IQR rule, the same method behind the whiskers on a box plot.
"The mean tells you the centre; the standard deviation tells you the story around it. Two datasets with the same average can be worlds apart in spread."
Descriptive, Not Inferential
It is worth being precise about what these numbers do and do not tell you. Everything this calculator computes is descriptive statistics — it faithfully summarises the data you entered, and nothing more. That is genuinely useful: descriptive statistics are how you make sense of a class's marks, a month of sales, a set of measurements, or a sports season. But they are not, by themselves, inferential statistics — they do not tell you whether a difference is significant, whether your sample is representative, or what a wider population looks like. Those questions depend on how the data were collected and on the sample size, and they need tests like confidence intervals and hypothesis tests, which live in dedicated statistics packages. Keeping that line clear is part of using statistics honestly. For the everyday job of understanding a set of numbers — their centre, their spread, and their outliers — this calculator gives you the complete descriptive picture instantly and privately, all in your browser.
10 Facts About Averages & Spread
There are three averages: mean, median, and mode — and they can disagree.
The median resists outliers, which is why incomes are usually reported as medians.
A dataset can have no mode, one mode, or several modes.
Standard deviation is the typical distance of a value from the mean.
Sample variance divides by n−1 (Bessel's correction); population by n.
The IQR is the spread of the middle half of the data (Q3 − Q1).
A value beyond 1.5×IQR from the quartiles is flagged as an outlier.
Two datasets can share a mean but have wildly different spread.
These are descriptive statistics — they summarise, they do not infer.
The same kernel powers the mean and quartiles across the site's tools.
Frequently Asked Questions
- The mean is the sum divided by the count (the everyday average), the median is the middle value when the data is sorted, and the mode is the value that appears most often. They agree for symmetric data but diverge when the data is skewed or has outliers — which is exactly when seeing all three is most useful. This calculator shows them together.
- Use the median when your data has outliers or is skewed — for example incomes or house prices, where a few very large values would pull the mean away from what is "typical". The median ignores how extreme the outliers are and reports the genuine middle, which is why it is the fairer summary in those cases.
- If your numbers are the entire group you care about, use the population version (divide by n). If they are a sample drawn from a larger group and you want to estimate that group's spread, use the sample version (divide by n−1, called Bessel's correction), which corrects a tendency to underestimate. The calculator shows both so you can pick the right one.
- Using the standard 1.5×IQR rule: any value below Q1 − 1.5×IQR or above Q3 + 1.5×IQR is flagged as an outlier. This is the same rule that draws the whiskers and dots on a box plot, and it is a robust way to spot values that stand apart from the bulk of the data.
- Yes. If several values tie for the highest frequency, the data is multimodal and the calculator lists all the modes. If no value repeats, there is no mode, and the tool says so rather than inventing one.
- Paste or type your numbers separated by commas, spaces, or new lines. A column copied straight from a spreadsheet works because each number is on its own line. The results update instantly as you edit.
- No — they are descriptive statistics, which summarise the numbers you entered. They do not tell you whether a difference is statistically significant or what a wider population looks like; those inferential questions depend on sample size and study design and need dedicated tests. Use these figures to understand your data, not to draw population-level conclusions on their own.
- Quartiles split sorted data into four equal parts: Q1 is the 25th percentile, Q2 the median, Q3 the 75th. The interquartile range (IQR) is Q3 − Q1 — the spread of the middle half of the data, a measure of spread that ignores extreme values. The calculator reports all of them.
- Yes. All calculations run in your browser — nothing is uploaded, stored, or logged — and the tool works offline once loaded. You can safely paste sensitive data.
- Completely free, with no account, sign-up, or limit. It runs entirely in your browser and collects no data. Use it as often as you like.
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