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 it’s far from zero, it indicates that the sample data do not have a normal distribution.

The test statistic * JB *is defined as:

* JB * =(n/6) * (S

^{2}+ (C

^{2}/4))

where:

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

Under the null hypothesis of normality, *JB ~ *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 under 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: **=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 don’t have sufficient evidence to say that the dataset is not normally distributed.