Normality Checker
Shapiro–Wilk test, skewness, kurtosis, histogram and Q–Q plot for your data.
Normality results
Shapiro–Wilk uses Royston's algorithm (the same as R's shapiro.test) and works for 3 to 5,000 values. Skewness and excess kurtosis are the sample-adjusted versions reported by SPSS and Excel.
Continue your work
- Outlier Detector — Find values that distort the shape.
- Mean, SD & SEM Calculator — Describe normally distributed data.
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Clear instructions
Find steps, examples and limitations below.
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Open the tool in a supported web browser.
Free to use
No sign-up required. Tool-specific limits may apply.
How to use the Normality Checker
Shapiro–Wilk test, skewness, kurtosis, histogram and Q–Q plot for your data.
- 1 Upload or paste your data and choose the column.
- 2 Read the Shapiro–Wilk result, skewness and kurtosis.
- 3 Check the histogram and Q–Q plot to judge the shape.
Example and practical tips
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.
Frequently asked questions
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.
Report an issue
Something broken or not quite right? Tell us and we will look into it.