Number Stats
Paste a list of numbers and get instant descriptive statistics: count, sum, mean, median, mode, range, variance, standard deviation, quartiles, IQR, outliers, skewness, kurtosis, and a live histogram.
About this tool
Descriptive statistics summarise a set of numbers with a few key values: the mean (average), median (middle value), mode (most frequent), range (max − min), and measures of spread like variance and standard deviation. Quartiles split the data into four equal parts and the interquartile range (IQR) identifies outliers.
Paste any list of numbers — separated by commas, spaces, tabs, semicolons, or new lines — and this tool computes all of the above plus a box plot and histogram. Example: paste 12, 14, 15, 15, 16, 18, 19, 22, 24, 25, 27, 28, 95 and you will see the value 95 flagged as an outlier because it sits more than 1.5 × IQR above the third quartile.
Skewness tells you whether the data leans left or right of the mean; kurtosis tells you how heavy the tails are compared to a normal distribution. Together they describe the shape of your data at a glance.
FAQ
What separators can I use? ›
Commas, spaces, tabs, semicolons, and new lines — or any mix of them. The tool extracts every number it can find, so you can paste raw output from a spreadsheet, a log file, or a database query.
What is the difference between sample and population standard deviation? ›
Sample standard deviation (n−1) divides by one less than the count and is the correct estimator when your data is a sample of a larger population. Population standard deviation (n) divides by the count and is used when you have every member of the population. The tool shows both.
How are outliers detected? ›
A value is flagged as an outlier if it falls below Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR. This is the Tukey fence method, the same rule used to draw the whiskers on the box plot.
Is my data sent anywhere? ›
No. All computation happens in your browser. Nothing is uploaded.