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The **Jarque-Bera test** is a goodness-of-fit test that determines whether or not sample data have skewness and kurtosis that matches a normal distribution.

The test statistic of the Jarque-Bera test is always a positive number and if itâ€™s far from zero, it indicates that the sample data do not have a normal distribution.

The test statisticÂ * JBÂ *is defined as:

* JBÂ * =(n/6) * (S

^{2}+ (C

^{2}/4))

where:

**n:**Â the number of observations in the sample**S:Â**the sample skewness**C:**the sample kurtosis

Under the null hypothesis of normality,Â *JB ~Â *X^{2}(2)

This tutorial explains how to conduct a Jarque-Bera test in Excel.

**Jarque-Bera test in Excel**

Use the following steps to perform a Jarque-Bera test for a given dataset in Excel.

**Step 1: Input the data.**

First, input the dataset into one column:

**Step 2: Calculate the Jarque-Bera Test Statistic.**

Next, calculate the JB test statistic. Column F shows the formulas used:

**Step 3: Calculate the p-value of the test.**

Recall that underÂ the null hypothesis of normality, the test statistic JB follows a Chi-Square distribution with 2 degrees of freedom. Thus, to find the p-value for the test we will use the following function in Excel:Â **=CHISQ.DIST.RT(JB test statistic, 2)**

The p-value of the test is **0.5921**. Since this p-value is not less than 0.05, we fail to reject the null hypothesis. We donâ€™t have sufficient evidence to say that the dataset is not normally distributed.