Test whether your data are normally distributed with the Shapiro–Wilk and Jarque–Bera tests, skewness and kurtosis, a histogram and a Q–Q plot.
About this tool
Shapiro–Wilk test, skewness, kurtosis, histogram and Q–Q plot for your data.
How to use Normality Checker
- Upload or paste your data and choose the column.
- Read the Shapiro–Wilk result, skewness and kurtosis.
- Check the histogram and Q–Q plot to judge the shape.
Worked example
Ages of 16 participants give Shapiro–Wilk W = 0.979, p = 0.956, with points close to the Q–Q line: consistent with a normal distribution.
Is the Shapiro–Wilk result the same as in R or SPSS?
Yes. It uses Royston’s algorithm, the same as R’s shapiro.test, for 3 to 5,000 values.
My large sample fails the test. Is that a problem?
With hundreds of values, tests flag tiny departures. Rely more on the Q–Q plot and the size of skewness and kurtosis.
- Normality Checker — Shapiro–Wilk test, skewness, kurtosis, histogram and Q–Q plot for your data.
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