Mean, Median and Mode Calculator
All three averages at once, and which one your data calls for.
Separated by commas, spaces or line breaks — anything that is not a number is ignored.
Slight right
- Median (middle value)
- 15.5
- Mode (most frequent)
- none — every value appears once
- Count
- 6
- Sum
- 108
- Range
- 4 to 42
- Standard deviation (sample)
- 13.490738
- Standard deviation (population)
- 12.315302
The reading is skew — how far the mean sits from the median relative to the spread. The further from symmetric, the more the median is the average worth quoting.
Every tool runs entirely in your browser. Your files are never uploaded to a server.
The mean is the total divided by the count, the median is the middle value once sorted, and the mode is the value appearing most often. They differ when data is skewed, and the median is the more honest average when it is.
How to use Mean, Median and Mode Calculator
- Paste your numbers. Separated by commas, spaces or line breaks. Anything that is not a number is ignored, so pasted data works as-is.
- Read all three averages. The mean sits at the top, with the median and mode beneath it along with the count and sum.
- Check the skew reading. The further the needle sits from symmetric, the more the mean is being pulled by outliers and the more the median is worth quoting.
About averages
The word average is ambiguous, and the ambiguity is regularly exploited. Mean, median and mode are all averages, they answer different questions, and choosing between them changes the story a dataset tells. The mean uses every value, which makes it sensitive to extremes: add one billionaire to a room of a hundred people and the mean wealth becomes meaningless while the median barely moves. That is precisely why income and house prices are reported as medians and why a mean quoted for either should be treated as a choice rather than a neutral fact. The mode is the only one of the three that works on data that is not numeric at all — the most common colour, the most frequent response — and it is the right average for anything categorical. The relationship between them is also informative. In symmetric data all three sit at roughly the same place. As data skews right, with a long tail of high values, the mean is pulled above the median; skewed left, the mean falls below it. The gap between mean and median, scaled by the spread, is a usable measure of that skew, which is what the reading on this page shows. Standard deviation then describes how far values typically sit from the mean, and the choice between the sample and population versions matters more than it looks: dividing by n underestimates the spread of a population when you only hold a sample of it, which is what the n minus one correction exists to fix.
Frequently asked questions
What is the difference between mean, median and mode?
When should I use the median instead of the mean?
What happens with an even number of values?
Can data have more than one mode?
Should I use sample or population standard deviation?
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