How to Perform a Correlation Test in Excel (Step-by-Step)

One way to quantify the relationship between two variables is to use the Pearson correlation coefficient which is a measure of the linear association between two variables.

It always takes on a value between -1 and 1 where:

  • -1 indicates a perfectly negative linear correlation between two variables
  • 0 indicates no linear correlation between two variables
  • 1 indicates a perfectly positive linear correlation between two variables

To determine if a correlation coefficient is statistically significant you can perform a correlation test, which involves calculating a t-score and a corresponding p-value.

The formula to calculate the t-score is:

t = r√(n-2) / (1-r2)


  • r: Correlation coefficient
  • n: The sample size

The p-value is calculated as the corresponding two-sided p-value for the t-distribution with n-2 degrees of freedom.

The following step-by-step example shows how to perform a correlation test in Excel.

Step 1: Enter the Data

First, let’s enter some data values for two variables in Excel:

Step 2: Calculate the Correlation Coefficient

Next, we can use the CORREL() function to calculate the correlation coefficient between the two variables:

The correlation coefficient between the two variables turns out to be 0.803702.

This is a highly positive correlation coefficient, but to determine if it’s statistically significant we need to calculate the corresponding t-score and p-value.

Step 3: Calculate the Test Statistic and P-Value

Next, we can use the following formulas to calculate the test statistic and the corresponding p-value:


The test statistic turns out to be 4.27124 and the corresponding p-value is 0.001634.

Since this p-value is less than .05, we have sufficient evidence to say that the correlation between the two variables is statistically significant. 

Additional Resources

How to Create a Correlation Matrix in Excel
How to Calculate Spearman Rank Correlation in Excel
How to Calculate Rolling Correlation in Excel

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