Last updated 3 September 2026
Three kinds of "average"
- Mean — add everything up, divide by how many there are. The one most people mean by "average."
- Median — sort the numbers and take the middle one (or the average of the two middle ones, for an even count). Not affected by extreme outliers.
- Mode — the value that shows up most often. There can be more than one, or none at all if nothing repeats.
A single "average" can hide a lot. A street where nine houses cost £200,000 and one costs £2,000,000 has a mean price over £380,000 — but a median of £200,000, which is what actually describes the typical house there.
Mean, median and mode are different answers
All three are called "the average" in everyday speech, and choosing the wrong one is how honest people produce misleading numbers. The mean adds everything and divides by the count. The median is the middle value once the data is sorted. The mode is the value that appears most often.
Consider nine employees earning $40,000 and one earning $500,000. The mean salary is $86,000, which describes nobody in the company — nine people earn far less and one earns far more. The median is $40,000, which describes a typical employee accurately. This is exactly why income, house price and response time figures are almost always reported as medians: a mean is pulled hard by extreme values, and a median is not.
Which one to use
Use the mean when the data is roughly symmetrical and you need a figure that can be combined arithmetically — it is the only one of the three where the average multiplied by the count returns the total. Use the median when the data is skewed or contains outliers you cannot justify removing. Use the mode for categorical data, where a mean is meaningless: the average of "red, red, blue" is not a number.
A useful diagnostic: calculate both the mean and the median. If they are close, the data is reasonably symmetrical and either will do. If they differ substantially, the data is skewed, and the direction tells you which way — a mean well above the median means a long tail of high values. That single comparison catches most of the situations where reporting an average would mislead.
Common questions
What's the difference between mean, median and mode?
Mean is the sum divided by the count — the everyday "average." Median is the middle value once everything is sorted. Mode is whichever value appears most often. They can all be different numbers for the same data set.
Why would I use median instead of mean?
Mean is pulled around by extreme values — one very large or small number can drag it far from what feels typical. Median ignores the size of outliers and just finds the middle, which is why income and house-price statistics are usually reported as medians.
What if there's no repeated value?
Then there is no mode, and the calculator says so rather than guessing. A mode only exists when at least one value appears more than once.
How do I enter the numbers?
Separate them with commas, spaces or new lines — any mix works. The calculator ignores anything that isn't a valid number.
When should I use the median instead of the mean?
Whenever the data is skewed or contains extreme values. Nine salaries of 40,000 and one of 500,000 produce a mean of 86,000, which describes nobody. The median of 40,000 describes a typical case, which is why incomes and house prices are usually reported that way.
Can I tell if my data is skewed?
Compare the mean and the median. If they are close, the data is roughly symmetrical. If the mean sits well above the median, there is a long tail of high values pulling it up; well below, and the tail runs the other way.
What is the mode useful for?
Categorical data, where a mean cannot be calculated — the most common colour, size or response option. It is also worth checking on numeric data, since a strong mode can reveal clustering that neither the mean nor the median shows.