Mean Calculator

The mean is the most common way to summarize a set of numbers — it is the sum of all values divided by how many values there are. This mean calculator finds the arithmetic mean of any list you enter, so you can skip the hand arithmetic and focus on what the result actually tells you.

How to use this calculator

1. Type your numbers into the Values box, separated by commas, spaces, or new lines — for example, 10, 20, 30, 40.
2. The Mean result updates immediately as you type.

There is no sample/population distinction for the mean itself. Unlike standard deviation, the average formula is the same whether your numbers represent a sample or the entire population.

Worked example

Take the dataset 4, 8, 6, 5, 3, 2, 8, 9, 2, 5 (10 values).

Step 1 — add all the values:

sum = 4 + 8 + 6 + 5 + 3 + 2 + 8 + 9 + 2 + 5 = 52

Step 2 — divide by the count (n = 10):

mean (x-bar) = sum / n = 52 / 10 = 5.2

The arithmetic mean is 5.2. As the NIST/SEMATECH e-Handbook on measures of location explains, the mean is the most common measure of central tendency because it accounts for every value in the dataset.

Frequently asked questions

What is the difference between mean, median, and mode?

The mean (the arithmetic average) adds all values and divides by the count. The median is the middle value when the data is sorted. The mode is the most frequently occurring value. Use the mean when your data has no extreme outliers; the median is usually a better choice when a few very large or very small values could pull the average away from the center of the data.

How do I find the mean step by step?

Add all the values together, then divide by how many values you have. For the numbers 3, 7, and 11: sum = 21, count = 3, mean = 21 / 3 = 7. This average calculator does both steps for you, for any size list.

Does the mean work with negative numbers?

Yes. The arithmetic mean treats negative numbers as signed values in the sum. For example, the mean of −4, 0, and 8 is (−4 + 0 + 8) / 3 = 4 / 3 ≈ 1.33.

When should I not use the mean?

Avoid the mean when your data is heavily skewed or contains outliers. A single extreme value can drag the mean far from where most of the data sits. In those situations, the median is a more representative summary of the typical value.