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The Jarque-Bera Test is a statistical method used to determine if a set of data follows a normal distribution. In order to perform this test in Excel, you will need to first organize your data in a single column. Then, use the “Data Analysis” tool to calculate the skewness and kurtosis of your data. Next, use the JARQUE.BERA function to calculate the test statistic and p-value. The p-value will indicate whether the data is normally distributed or not. A low p-value suggests that the data does not follow a normal distribution. This test can be useful in various fields such as finance, economics, and social sciences to assess the validity of certain assumptions.
Perform a Jarque-Bera Test in Excel
The Jarque-Bera test is a goodness-of-fit test that determines whether or not sample data have skewness and kurtosis that matches a .
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) * (S2 + (C2/4))
where:
- n: the number of observations in the sample
- S: the sample skewness
- C: the sample kurtosis
Under the null hypothesis of normality, JB ~ X2(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.
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.