Descriptive Statistics Calculator

Mean, median, mode, standard deviation, variance, quartiles — from any dataset.

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Calculate mean, median, standard deviation and more

Numeric data (one number per line, or separated by commas/spaces)

Upload CSV

Decimals: use a period or a comma — 99.5 or 99,5. Accepts newline, comma, space, or tab separators.

Central tendency & range

—Count (n)

—Sum

—Mean

—Median

—Mode

—Min

—Max

—Range

Dispersion

—Variance (pop.)

—Variance (sample)

—Std Dev (pop.)

—Std Dev (sample)

—Standard error

—Coeff. of variation

Shape & quartiles

—Skewness

—Kurtosis (excess)

—Q1 (25th pctile)

—Q2 (median)

—Q3 (75th pctile)

—Interquartile range

Descriptive statistics in Excel and Google Sheets

Excel and Google Sheets have built-in functions for nearly every descriptive statistic. Put your data in the range A1:A100 (or whatever fits) and use the formulas below.

=COUNT(A1:A100)          Count
=SUM(A1:A100)           Sum
=AVERAGE(A1:A100)       Mean
=MEDIAN(A1:A100)        Median
=MODE.SNGL(A1:A100)     Mode (single)
=MODE.MULT(A1:A100)     Mode (all — array)
=MIN(A1:A100)           Min
=MAX(A1:A100)           Max
=MAX(A1:A100)-MIN(A1:A100)  Range

=VAR.P(A1:A100)         Population variance (÷n)
=VAR.S(A1:A100)         Sample variance (÷(n−1))
=STDEV.P(A1:A100)       Population std dev
=STDEV.S(A1:A100)       Sample std dev

=QUARTILE.INC(A1:A100,1)    Q1 (25th percentile)
=QUARTILE.INC(A1:A100,2)    Q2 (median)
=QUARTILE.INC(A1:A100,3)    Q3 (75th percentile)

=SKEW(A1:A100)          Skewness (sample)
=KURT(A1:A100)          Kurtosis (excess, sample)

Formulas for A1:A100. In Sheets, KURT is the same; PERCENTILE.INC exists as PERCENTILE.

MODE.MULT returns a vertical array of all modes. In Excel, select several cells in a column, type the formula, and confirm with Ctrl+Shift+Enter (or just Enter in Microsoft 365 with dynamic arrays). In Google Sheets, MODE.MULT does not exist: use =UNIQUE(FILTER(A1:A100, COUNTIF(A1:A100, A1:A100)=MAX(COUNTIF(A1:A100, A1:A100)))).

Descriptive statistics in SQL (PostgreSQL)

PostgreSQL provides aggregate functions for the most common statistics. Given a table data with a numeric column value, this query returns all the indicators in a single row.

SELECT
    COUNT(value)                                    AS n,
    SUM(value)                                      AS total,
    AVG(value)                                      AS mean,
    PERCENTILE_CONT(0.5)  WITHIN GROUP (ORDER BY value) AS median,
    MODE()                WITHIN GROUP (ORDER BY value) AS mode,
    MIN(value)                                      AS min_val,
    MAX(value)                                      AS max_val,
    MAX(value) - MIN(value)                         AS range,
    VAR_POP(value)                                  AS var_pop,
    VAR_SAMP(value)                                 AS var_samp,
    STDDEV_POP(value)                               AS stddev_pop,
    STDDEV_SAMP(value)                              AS stddev_samp,
    STDDEV_SAMP(value) / SQRT(COUNT(value))         AS std_error,
    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY value) AS q1,
    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY value) AS q3
FROM data;

PostgreSQL 9.4+. PERCENTILE_CONT requires a WITHIN GROUP clause. For MySQL, use STDDEV_POP(), STDDEV_SAMP(), VARIANCE(), and VAR_SAMP(); percentiles need a window subquery.

PostgreSQL had no direct MODE() aggregate before version 9.4; since then use MODE() WITHIN GROUP (ORDER BY value). For mode in MySQL, group by value, count, and filter for the maximum.

About this descriptive statistics calculator

Paste or type a list of numbers and get a full descriptive statistics summary: count, sum, mean, median, mode, range, minimum, maximum, population and sample variance, population and sample standard deviation, standard error, coefficient of variation, skewness, kurtosis, and the five-number summary (Q1, Q2, Q3, IQR). You can also upload a CSV file with a single column of numbers.

Every calculation runs locally in your browser — your data never leaves your device. The tool includes ready-to-use Excel and Google Sheets formulas (AVERAGE, MEDIAN, STDEV.S, STDEV.P, QUARTILE.INC) and SQL equivalents (AVG, STDDEV_POP, PERCENTILE_CONT) so you can reproduce the same results in your own workflow.

Reference tables

Z-Score Table — Standard Normal DistributionLook up the area to the left of any z-score, positive or negative, to four decimal places.

FAQ

What is the difference between population and sample standard deviation?

Population standard deviation (σ) divides by N and assumes you have every value in the group. Sample standard deviation (s) divides by N−1 and corrects for the fact that a sample underestimates spread. Use sample when your data is a subset of a larger group — which is almost always the case.

What do skewness and kurtosis tell me?

Skewness measures asymmetry: positive means a right tail, negative means a left tail, zero means symmetric. Kurtosis measures tail heaviness: a value above 3 (excess above 0) means heavier tails than a normal distribution, below means lighter. Together they tell you whether the mean and standard deviation are good summaries or whether outliers dominate.

Can I use this with data from a spreadsheet?

Yes. Copy a column from Excel or Google Sheets, paste it into the input box, and the calculator parses one number per line. You can also upload a CSV file directly.