Average Calculator

Calculate mean, median, mode, range and standard deviation for any set of numbers

// Enter Your Numbers

Accepts comma, space or line-separated values. Duplicate values are allowed.

Statistical Measures Explained

Different types of "average" tell you different things about a dataset. No single measure is always best — the right choice depends on the nature of your data and what question you're trying to answer.

Formulas

Mean vs Median — When to Use Each

The mean is sensitive to outliers. A single very high or low value can pull it significantly. The median is resistant to outliers — it's a better measure of central tendency for skewed data like incomes, house prices or response times.

Example: Five salaries of £25k, £28k, £30k, £32k, £200k. Mean = £63k (misleading). Median = £30k (more representative).

Population vs Sample Std Deviation

Use population std deviation (σ) when you have data for every member of the group. Use sample std deviation (s) when your data is a sample drawn from a larger population — it uses n−1 in the denominator (Bessel's correction) to give an unbiased estimate.

Note: Results are rounded to 6 significant figures for display. Calculations use full floating-point precision internally. Maximum 1,000 data points.

// Outliers

A single extreme value can skew the mean dramatically. When in doubt, check the median too — if they differ significantly, your data is skewed.

// IQR

The interquartile range (IQR = Q3−Q1) measures spread for the middle 50% of data. It's more robust than range when outliers exist.

// Sample vs Population

If your numbers are a sample (not the whole group), use sample std deviation (s) — it gives a less biased estimate of the true spread.

// No Mode

If every value appears exactly once, there is no mode. If multiple values tie for most frequent, all are modes (multimodal dataset).