Finding the Pearson Correlation

Published: 15 Feb 2017
Last Modified Date: 15 Feb 2017


How to find the Pearson correlation of two measures in Tableau Desktop.


Tableau Desktop


Step 1: Create a scatterplot

This example uses Superstore sample data. 
Drag Profit to Columns and Sales to Rows.
Drag Customer Name to Detail.
In the Analysis menu, uncheck Aggregate Measures. 
Right-click the view and choose Trend Lines > Show Trend Lines.
Right-click the view again and select Trend Lines > Describe Trend Model. 

Step 2: Calculate the correlation

Locate the R-Squared value in the Describe Trend Model dialog box. In this example, the R-Squared value is 0.229503.
User-added image
Using a calculator or other program, calculate the square root of the R-squared value. This is your correlation (r). Rounded to two digits, the value in this example is 0.48. 

Additional Information

A correlation, r, is a single number that represents the degree of relationship between two measures. The correlation coefficient is a value such that -1 <= r <= 1.

A positive correlation indicates a relationship between x and y measures such that as values of x increase, values of y also increase.

A negative correlation indicates the opposite—as values of x increase, values of y decrease.

The closer the correlation, r, is to -1 or 1, the stronger the relationship between x and y.

If r is close to or equal to 0, there is a weak relationship or no relationship between the measures.

As a general rule, you can interpret r values this way:

  • +.70 or higher indicates a very strong positive relationship
  • +.40 to +.69 indicates a strong positive relationship
  • +.20 to +.39 indicates a moderate positive relationship
  • -.19 to +.19 indicates no or a weak relationship
  • -.20 to -.39 indicates a moderate negative relationship
  • -.40 to -.69 indicates a strong negative relationship
  • -.70 or lower indicates a very strong negative relationship
Did this article resolve the issue?