Descriptive Statistics Calculator
Paste your numbers below — separated by spaces, commas or new lines — and get a full set of summary statistics instantly. Nothing is uploaded; the calculation happens entirely in your browser.
How to use it
What the numbers mean
Descriptive statistics summarise a dataset in a few numbers, split into two families:
- Centre: the mean (average, sensitive to outliers) and the median (middle value, robust to them). When mean and median diverge sharply, your data is skewed.
- Spread: the standard deviation and variance measure typical distance from the mean; the IQR (Q3 − Q1) measures the spread of the middle half and, like the median, resists outliers. The standard error describes the precision of the mean itself, not the spread of the data.
Quartiles here use R’s default (type 7) definition, so results match quantile() in R exactly.
Do it in R
x <- c(23, 19, 25, 22, 30, 18, 27, 24, 21, 26)
summary(x); sd(x); IQR(x)FAQ
Frequently asked questions
Mean or median — which should I report?
Report both, but lead with the median for skewed data or when outliers are present, and the mean for roughly symmetric data. The gap between them is itself informative.
Standard deviation vs standard error?
Standard deviation describes the spread of the data; standard error describes the uncertainty of the mean and shrinks as the sample grows. Don’t use one where you mean the other.
Summary statistics are step one. When you need tests, models and a written report, we take it from here.