In statistics, the Jarque–Bera test is a goodness-of-fit test of whether sample data have skewness and kurtosis matching a normal distribution. The test is named after Carlos Jarque and Anil K. Bera.

Skewness and kurtosis are both necessary measures of a distribution's shape. Skewness measures the asymmetry of a distribution. Kurtosis measures the heaviness of a distribution's tails relative to a normal distribution.

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