Skip to content
MasterMath

Mean Median Mode Calculator

Mean, median, mode, range and standard deviation from a list of values. Three different answers to 'what is typical', and they often disagree.

Mean

—

Mean—
Median—
Mode—
How many values—
Range—
Sample standard deviation—

How this was worked out

    The rule

    mean = sum ÷ count · median = the middle value once sorted

    Why it works

    The mean balances the values, the median splits them in half, and the mode is whichever occurs most. They describe the centre in genuinely different ways, and which one to use depends on the shape of the data.

    How to do it by hand

    1. Add the values and divide by how many there are for the mean
    2. Sort them and take the middle one for the median
    3. The most frequent value is the mode
    4. The standard deviation measures how spread out they are

    What is worth knowing

    The mean is the one to distrust with skewed data, because a single extreme value drags it. Household income is the standard case: the mean is far above the median because a small number of very high incomes pull it up, which is why the median is what gets reported. The mode is the only one that works on categories rather than numbers — you can have a most common colour but not an average one. As for standard deviation, this uses the sample version, dividing by n−1, which is the right choice whenever the data is a sample rather than the whole population.

    Frequently asked questions

    When should I use the median instead of the mean?

    Whenever the data is skewed or has outliers. Income is the classic case: the mean is far above the median.

    Can there be more than one mode?

    Yes. Data with two equally common values is bimodal, and some data has no mode at all.

    What is the difference between sample and population standard deviation?

    The sample version divides by n−1 rather than n, which corrects a bias when the data is only a sample.

    What does the standard deviation tell me?

    How spread out the values are. A small one means they cluster near the mean; a large one means they scatter.