Statistics Calculator

The Statistics Calculator is a free online tool that comprehensive statistical analysis: mean, median, mode, variance, std dev, iqr, quartiles, percentiles, outlier detection, skewness, kurtosis, histogram, and box plot.. It runs entirely in your browser with no installation or sign-up needed.

Arithmetic (standard), geometric (for growth rates, positive values only), and harmonic (for rates/ratios, positive values only).

IQR method: values below Q1 - 1.5*IQR or above Q3 + 1.5*IQR are flagged. Highlighted in the data table and shown as dots on the box plot.

Skewness: near zero = symmetric, negative = left-skewed, positive = right-skewed. Excess kurtosis: positive = heavier tails than normal (leptokurtic), negative = lighter tails (platykurtic).

Yes, the Statistics Calculator is 100% free with no registration, no hidden fees, and no usage limits. All processing happens locally in your browser, ensuring complete privacy.

Absolutely. The Statistics Calculator processes everything client-side in your browser. No data is uploaded to or stored on any server. Your content remains private on your device at all times.

Yes, the Statistics Calculator is fully responsive and works on smartphones and tablets. You can use it on any device with a modern web browser -- no app download required.

No account or registration is needed. Simply open the Statistics Calculator in your browser and start using it immediately. There are no sign-up walls or usage restrictions.

The Statistics Calculator uses industry-standard formulas and algorithms to ensure accurate results. However, for critical financial or medical decisions, always consult a qualified professional.

Simply enter your input in the provided field, adjust any settings to your preference, and the tool will process it instantly. You can then copy the result to your clipboard or download it.

The mean is the arithmetic average: add every value and divide by how many there are. The median is the middle value once the data is sorted, so half the numbers fall below it and half above; with an even count it averages the two middle values. The mode is the value that appears most often, and a dataset can have one mode, several, or none. The key practical difference is sensitivity to extreme values: the mean gets pulled toward outliers, while the median stays put, which is why median income is often more representative than mean income. The mode simply reflects the most common observation. This calculator reports all three at once, plus geometric, harmonic, and midrange averages, so you can compare them and pick the measure of central tendency that best fits your data. Paste your numbers above to see them update instantly.

It depends on whether your numbers are the entire group or just a subset of a larger one. Use population standard deviation (dividing the squared deviations by n) when your data covers every member you care about, such as the test scores of one specific class. Use sample standard deviation (dividing by n minus 1, known as Bessel's correction) when your numbers are a sample drawn from a bigger population and you want to estimate that population's spread; the smaller divisor corrects for the tendency of a sample to underestimate true variability. Sample formulas need at least two values, so a single number returns only the population figure. Most research and survey work uses the sample version. This tool shows both side by side, along with population and sample variance, so you never have to guess which divisor applies. Enter your data above to compare them.

Quartiles and percentiles mark positions within sorted data. A percentile is the value below which a given share of observations falls; the 90th percentile is the point under which 90 percent of values sit. Quartiles are simply the 25th, 50th, and 75th percentiles, labeled Q1, Q2 (the median), and Q3, splitting the data into four equal parts. This calculator finds them by sorting your numbers and using linear interpolation: it locates the fractional rank for the target percentile and, when that rank lands between two data points, blends them proportionally rather than rounding to the nearest one. That gives smooth, consistent results even for small datasets. It reports Q1, Q2, Q3 plus the 10th, 25th, 50th, 75th, 90th, 95th, and 99th percentiles together. Paste your values above and open the Position tab to see every quartile and percentile at once.

A box plot summarizes a distribution using the five-number summary: minimum, first quartile (Q1), median, third quartile (Q3), and maximum. The box spans Q1 to Q3, so its width is the interquartile range and contains the middle 50 percent of your values. A line inside the box marks the median, and if it sits off-center the data is skewed toward the longer side. The whiskers extend to the most extreme values still inside the outlier fences, and any points beyond those fences are drawn as separate dots, making unusual observations easy to spot at a glance. Box plots are ideal for comparing spread and symmetry without assuming a particular distribution shape. This calculator builds the box plot automatically from your numbers and marks any IQR-detected outliers on it. Enter your data above and check the Position tab to view the box plot and its five-number summary.

The coefficient of variation (CV) expresses the standard deviation as a percentage of the mean, giving you a measure of relative spread rather than absolute spread. Because it is unitless, it lets you compare the variability of datasets that use different units or operate on very different scales; comparing the consistency of monthly rainfall to daily stock returns, for example, makes little sense with raw standard deviations but works with CV. A higher percentage means more variability relative to the average, while a lower one indicates tighter, more consistent data. CV is most meaningful for positive data on a ratio scale and becomes unreliable when the mean is near zero, since dividing by a tiny mean inflates the result. This calculator computes CV from the sample standard deviation automatically alongside variance, range, and mean absolute deviation. Paste your numbers above to see the coefficient of variation update with the rest of the dispersion metrics.