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Statistics on data

Five-number summary calculator online

Five numbers that describe a distribution without assuming anything about its shape: the two ends, the two quartiles and the middle. Together they say where the data starts, where the bulk of it sits and where it stops — which is more than a mean and a standard deviation can honestly claim on skewed data.

Your data never leaves this device

Your data

Paste a table straight from Excel or Google Sheets, or drop a CSV file. Nothing is uploaded anywhere — the whole calculation runs inside this browser tab.

CSV, TSV or plain text. Files saved in windows-1251 are detected and re-read automatically, so Cyrillic headers do not turn into garbage.

Parsing options

Columns

Result

The drawing library is downloaded only when you press the button, and only on this page.

This page has no server side at all. The table you paste is parsed by JavaScript inside your own browser, the chart is drawn on a canvas element on your machine, and the export file is assembled locally. Nothing is uploaded, stored or written to any log. You can disconnect from the network after the page has loaded and everything will still work — which is the simplest way to verify the claim yourself.

Facts and limits of this method

The five numbers Minimum, Q1, median, Q3, maximum
Also returned IQR (Q3 − Q1) and the full range (max − min)
Quantile definition R type 7, identical to Excel PERCENTILE.INC
Distribution assumptions None — this is the summary you use when you do not know the shape
Relation to the box plot These five numbers are exactly what a box plot draws
Minimum rows 2

When it misleads you

How it is calculated

The values are sorted once. The minimum and maximum are the ends of that sorted list, the median is the middle, and Q1 and Q3 are the quartiles computed with the R type 7 definition — the same one Excel uses for PERCENTILE.INC, so the numbers reconcile with your spreadsheet.

The interquartile range, Q3 − Q1, is added because it is the number that actually gets used. It covers the middle half of the observations and is the robust alternative to the standard deviation when the data is skewed or contains outliers.

The full range, maximum minus minimum, is reported separately and should be treated with suspicion: it is determined entirely by the two most extreme observations and grows mechanically as you collect more data, even when nothing about the process has changed.

These are exactly the five numbers a box plot draws, which is why the box plot tool is linked from this page. The summary is the table; the box plot is the same information as a picture.

Questions and answers

Why five numbers and not the mean and standard deviation?

Because the five-number summary makes no assumption about the shape of the distribution. The mean and standard deviation describe a symmetric single-peaked shape well and everything else badly.

Is this the same as a box plot?

Yes, in content. A box plot draws these five numbers — the box spans Q1 to Q3, the line inside is the median, and the whiskers reach towards the extremes. The box plot tool on this site draws it.

Why is my range so much wider than my IQR?

Because the range is set by the two most extreme values and the IQR ignores them. A large gap between the two is a strong hint that outliers are present; the outlier detection tool will identify them.

Do I need to check for normality first?

No, and that is the point. This summary is valid for any distribution, which is why it is the safe first thing to compute on unfamiliar data.

Does my data leave the browser?

No. Sorting and quantile interpolation both happen locally.

The opposite tool

Need it the other way round? Quartiles and percentiles Where your data sits, from P5 to P99

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