A **normal probability plot** can be used to determine if the values in a dataset are roughly normally distributed.

This tutorial provides a step-by-step example of how to create a normal probability plot for a given dataset in Excel

**Step 1: Create the Dataset**

First, let’s create a fake dataset with 15 values:

**Step 2: Calculate the Z-Values**

Next, we’ll use the following formula to calculate the z-value that corresponds to the first data value:

=NORM.S.INV((RANK(A2, $A$2:$A$16, 1)-0.5)/COUNT(A:A))

We’ll copy this formula down to each cell in column B:

**Step 3: Create the Normal Probability Plot**

Next, we’ll create the normal probability plot.

First, highlight the cell range A2:B16 as follows:

Along the top ribbon, click the **Insert** tab. Under the **Charts** section, click the first option under **Scatter**.

This automatically produces the following chart:

The x-axis displays the ordered data values and the y-value displays their corresponding z-values.

Feel free to modify the title, axes, and labels to make the plot more aesthetically pleasing:

**How to Interpret a Normal Probability Plot**

The way to interpret a normal probability plot is simple: if the data values fall along a roughly straight line at a 45-degree angle, then the data is normally distributed.

In our plot above we can see that the values tend to deviate from a straight line at a 45-degree angle, especially on the tail ends. This likely indicates that the data is not normally distributed.

Although a normal probability plot isn’t a formal statistical test, it offers an easy way to visually check whether or not a data set is normally distributed.

If you’re looking for a formal normality test, read this tutorial on how to perform a normality test in Excel.

**Additional Resources**

How to Make a Bell Curve in Excel

How to Make a Frequency Polygon in Excel

How to Create a Log-Log Plot in Excel