Statistics Calculator
Calculate descriptive statistics online: count, sum, mean, median, mode, min, max, range, variance, standard deviation (population + sample), and sum of squares. Multi-modal aware. 100% browser-based, no signup.
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Descriptive Stats
Count (n), sum, mean, median, mode, min, max, range, variance, standard deviation, and sum of squares — all computed from your list in one shot.
Multimodal Mode
Mode shows every value that ties for highest frequency. If your dataset has two modes (bimodal) or more, all of them are listed. If every value is unique, "no mode" is shown.
Pop. & Sample Variance
Both population (÷n) and sample (÷n−1) variance and standard deviation are shown, so the tool works for both complete-population and inferential-sample use cases.
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Your numbers stay in your browser. No data is uploaded to a server, no signup required, and there is no daily limit.
How do I enter numbers?
Separate numbers with any combination of commas, spaces, semicolons, or newlines. For example: "4, 8, 15, 16, 23, 42" or one per line. The calculator parses each token individually.
What is the difference between population and sample variance?
Population variance divides the sum of squared deviations by n (the full count). Sample variance divides by n−1 (Bessel's correction) to give an unbiased estimate from a sample. The calculator shows both.
How is the median calculated for an even count?
For an odd number of values, the median is the middle value after sorting. For an even count, the median is the average of the two middle values — e.g. for [1,2,3,4] the median is (2+3)/2 = 2.5.
What happens when there are multiple modes?
If two or more values share the highest frequency, all of them are shown as modes. The dataset is then "multimodal". If every value appears exactly once (all unique), there is no mode and the calculator shows "No mode (all values unique)".
What is "sum of squares"?
Sum of squares is the sum of the squares of each value (Σx²). It is distinct from the sum of squared deviations (Σ(x−mean)²), which is used to compute variance. Both are intermediate quantities that other statistics build on.
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