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Shapiro-Wilk Normality Test

Normality tests online with Q-Q plot. Shapiro Wilk for small to medium samples.

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When to use it

Use to test whether a sample comes from a normal distribution before running a parametric test (t-test, ANOVA, regression). Shapiro-Wilk has the best power for small to medium samples (n up to about 5000) and is the most widely cited normality test in agronomy and biology journals.

When NOT to use it

Do not use as the only check; pair with a Q-Q plot. Do not use on very large samples (n > 5000) where the test rejects trivial deviations of no practical importance. For tail-sensitivity prefer Anderson-Darling. For checking normality of regression residuals, run the test on residuals not on raw Y.

What you get

The W statistic, the p-value, sample size, mean and SD, plus a normal Q-Q plot of the data with the reference line. Output flags when n is outside the test's recommended range.

How to interpret the output

Reject normality when p is below alpha. A non-rejection is not proof of normality, only that the test could not detect deviation. For ANOVA practical guidance: mild non-normality is tolerable when groups are balanced and n is moderate; severe right-skew suggests a log transform. Always read the Q-Q plot in addition to the p (Royston 1995 recommends visual checks as primary, formal tests as confirmation).

Common pitfalls

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References

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