What's the difference between population and sample values?

Population variance/SD divides by n; sample versions divide by n−1. Use the sample version when your data is a subset of a larger group.

How is the median or a quartile computed for even-sized data?

By linear interpolation between the two surrounding values, the standard method used by most statistics tools.

Is my data uploaded anywhere?

No. All calculations run in your browser and nothing is sent to a server.

Which quartile method does it use?

Quartiles are computed by linear interpolation between the two nearest ordered values - the same method as Excel's PERCENTILE.INC, R's default type 7 and NumPy's default. It matters because there are at least nine accepted definitions, and they disagree on small datasets, so a quartile from a different tool can legitimately differ from this one.

How should I enter my data?

Paste the numbers in and the tool separates them itself, so a column copied out of a spreadsheet works as well as a comma-separated line. Anything that is not a number is skipped rather than treated as zero, which keeps a stray header row from dragging the mean down without you noticing.

When should I look at the median instead of the mean?

Whenever a few extreme values would drag the average somewhere unrepresentative - salaries, house prices, response times. The mean moves with every outlier; the median only cares about the middle of the order. A large gap between the two is itself the signal that your data is skewed and the mean alone will mislead.

📊 Statistics Calculator

Paste or type a list of numbers and get a full descriptive-statistics summary in one place: count, sum, mean, median, mode, min, max, range, population and sample variance, population and sample standard deviation, and the quartiles Q1/Q3 with IQR. Everything is computed live in your browser — free, private, and offline-capable.

Enter your numbers

Separate values with commas, spaces, or new lines.

Private by design. This tool runs entirely in your browser — nothing you enter is uploaded or stored, and it works offline.

About

The calculator accepts numbers separated by commas, spaces or new lines, so you can paste a column straight from a spreadsheet. It reports both the population and the sample versions of variance and standard deviation — the sample version divides by n−1 (Bessel's correction) and is the right choice when your data is a sample of a larger group. Quartiles use linear interpolation. All results can be copied at once for pasting into a report.

How to use

Paste or type your numbers, separated by commas, spaces, or new lines.
Results appear instantly — mean, median, mode, SD, variance, quartiles and more.
Use 'Copy all' to grab every statistic as text for your report or homework.

FAQ

What's the difference between population and sample values?: Population variance/SD divides by n; sample versions divide by n−1. Use the sample version when your data is a subset of a larger group.
How is the median or a quartile computed for even-sized data?: By linear interpolation between the two surrounding values, the standard method used by most statistics tools.
Is my data uploaded anywhere?: No. All calculations run in your browser and nothing is sent to a server.
Which quartile method does it use?: Quartiles are computed by linear interpolation between the two nearest ordered values - the same method as Excel's PERCENTILE.INC, R's default type 7 and NumPy's default. It matters because there are at least nine accepted definitions, and they disagree on small datasets, so a quartile from a different tool can legitimately differ from this one.
How should I enter my data?: Paste the numbers in and the tool separates them itself, so a column copied out of a spreadsheet works as well as a comma-separated line. Anything that is not a number is skipped rather than treated as zero, which keeps a stray header row from dragging the mean down without you noticing.
When should I look at the median instead of the mean?: Whenever a few extreme values would drag the average somewhere unrepresentative - salaries, house prices, response times. The mean moves with every outlier; the median only cares about the middle of the order. A large gap between the two is itself the signal that your data is skewed and the mean alone will mislead.