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Descriptive Statistics Calculator

Paste a column of numbers and get the complete descriptive summary in one shot: mean with standard error and 95% confidence interval, standard deviation and variance, median with quartiles and IQR, minimum/maximum/range, and the shape measures skewness and kurtosis (computed with the SPSS/Excel type-2 formulas, so the numbers match what your course or supervisor expects). The Shapiro-Wilk normality test runs automatically on the same data — the check you need before deciding between parametric tests (t-test, ANOVA) and their non-parametric alternatives. Everything is computed in your browser; your data never leaves your device.

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Frequently asked questions

How do I report descriptive statistics in APA 7 format?

Means and standard deviations are reported as M and SD, e.g.: "Participants (N = 15) responded quickly on average (M = 14.81, SD = 4.47, 95% CI [12.34, 17.29])." The copy button gives you exactly this M/SD/N string; the AI Report builds full APA descriptive tables.

When should I report the median instead of the mean?

When the distribution is skewed or contains outliers — the mean chases extreme values while the median does not. A large gap between mean and median (or |skewness| > 1) is a signal to report median and IQR.

How do I interpret skewness and kurtosis?

Skewness measures asymmetry: positive = long right tail, negative = long left tail; |values| < 1 are usually acceptable for normality-based tests. Excess kurtosis compares tail weight to the normal distribution: positive = heavier tails and more outliers.

What does the Shapiro-Wilk test tell me?

It tests the null hypothesis that your data come from a normal distribution. p < .05 suggests non-normality — relevant for choosing parametric vs non-parametric tests. With large samples it flags even trivial deviations, so pair it with the skewness/kurtosis values above.