5 Ways To Test Normality In Excel

Testing for normality is a crucial step in statistical analysis, as many statistical tests assume that the data follows a normal distribution. In Excel, there are several methods to test for normality, each with its own strengths and limitations. In this article, we will explore five ways to test for normality in Excel.

Normal distribution is a fundamental concept in statistics, and it is essential to understand whether your data follows a normal distribution or not. Non-normal data can lead to incorrect conclusions and misleading results. Fortunately, Excel provides several tools to help you determine if your data is normally distributed.

What is Normal Distribution?

A normal distribution, also known as a Gaussian distribution or bell curve, is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In a normal distribution, about 68% of the data falls within one standard deviation of the mean, about 95% falls within two standard deviations, and about 99.7% falls within three standard deviations.

Method 1: Visual Inspection using Histograms

One of the simplest ways to test for normality is to create a histogram of your data. A histogram is a graphical representation of the distribution of your data. To create a histogram in Excel, go to the "Insert" tab, click on "Bar Chart," and then select "Histogram." If your data is normally distributed, the histogram should resemble a bell curve.

How to Create a Histogram in Excel

Select the data range that you want to analyze.
Go to the "Insert" tab in the ribbon.
Click on "Bar Chart" and then select "Histogram."
Right-click on the histogram and select "Format Data Series."
In the "Format Data Series" dialog box, select "Normal" under "Distribution."

Method 2: Shapiro-Wilk Test

The Shapiro-Wilk test is a statistical test used to determine whether a dataset is normally distributed. The test produces a W-statistic, which ranges from 0 to 1. A W-statistic close to 1 indicates that the data is normally distributed. To perform the Shapiro-Wilk test in Excel, you can use the "Analysis ToolPak" add-in.

How to Perform the Shapiro-Wilk Test in Excel

Select the data range that you want to analyze.
Go to the "Data" tab in the ribbon.
Click on "Data Analysis" and then select "Shapiro-Wilk Test."
In the "Shapiro-Wilk Test" dialog box, select the data range and click "OK."

Method 3: Q-Q Plot

A Q-Q plot (Quantile-Quantile plot) is a graphical method to compare the distribution of your data with a normal distribution. If your data is normally distributed, the points on the Q-Q plot should lie close to a straight line.

How to Create a Q-Q Plot in Excel

Select the data range that you want to analyze.
Go to the "Insert" tab in the ribbon.
Click on "Scatter Chart" and then select "Q-Q Plot."
Right-click on the Q-Q plot and select "Format Data Series."
In the "Format Data Series" dialog box, select "Normal" under "Distribution."

Method 4: Skewness and Kurtosis

Skewness and kurtosis are statistical measures that can help you determine if your data is normally distributed. Skewness measures the asymmetry of the distribution, while kurtosis measures the "tailedness" of the distribution. For a normal distribution, the skewness should be close to 0, and the kurtosis should be close to 3.

How to Calculate Skewness and Kurtosis in Excel

Select the data range that you want to analyze.
Go to the "Formulas" tab in the ribbon.
Click on "More Functions" and then select "Statistical."
Select "SKEW" for skewness and "KURT" for kurtosis.

Method 5: Anderson-Darling Test

The Anderson-Darling test is a statistical test used to determine whether a dataset is normally distributed. The test produces an A-statistic, which ranges from 0 to infinity. A small A-statistic indicates that the data is normally distributed.

How to Perform the Anderson-Darling Test in Excel

Select the data range that you want to analyze.
Go to the "Data" tab in the ribbon.
Click on "Data Analysis" and then select "Anderson-Darling Test."
In the "Anderson-Darling Test" dialog box, select the data range and click "OK."

Normal Distribution Image Gallery

We hope this article has helped you understand the different methods to test for normality in Excel. Remember to choose the method that best suits your data and analysis needs. If you have any questions or need further assistance, please don't hesitate to ask.

Take a moment to share your thoughts and experiences with normality testing in the comments section below. Have you used any of these methods in your own analysis? Do you have any favorite tools or techniques for testing normality? Share your insights and help others learn from your experiences!