How to Add R-Squared to Power BI Scatter Plots Using DAX

When analyzing correlations in Power BI, you can enable a trend line in scatter plots. This helps visualize the relationship between two variables. However, Power BI does not natively provide the R-squared (R²) value, which is crucial in determining how well the regression line fits the data.

With this custom DAX measure, we can calculate and display the R² value, filling the missing functionality in Power BI.

What is R-Squared?

R-squared (R²) measures how well the independent variable (X) explains the dependent variable (Y). It ranges from 0 to 1 (or 0% to 100% when displayed as a percentage).

• 🔵 R² = 1 (100%) → Perfect fit, all data points lie exactly on the trend line.
• 🟠 R² = 0 → No correlation, the trend line does not explain any variance.
• 🟢 Higher R² → Stronger relationship between variables.

How to Implement R-Squared in Power BI

Use the following DAX measure to calculate R² for a scatter plot:

R Squared Value = 
// STEP 1 : GET THE MEAN FOR X AXIS
// STEP 2 : GET THE MEAN FOR Y AXIS
// STEP 3 : GET THE SUMX FOR EACH  (X - X MEAN )  * ( Y - Y MEAN )
// STEP 4 : SQRT( SUMX(  (X - X MEAN) SQUARED) *  SUMX(  (Y - Y MEAN) SQUARED)
// STEP 5 : STEP 3 / STEP 4 IS THE R SQUARED VALUE

VAR __muX = CALCULATE(AVERAGE(salary_data[YearsExperience] ))
VAR __muY = CALCULATE(AVERAGE(salary_data[Salary]))

VAR __num = SUMX(salary_data,(salary_data[YearsExperience] - __muX) * (salary_data[Salary] - __muY))

VAR __denum = SQRT(SUMX(salary_data,(salary_data[YearsExperience]- __muX) ^ 2) *
                   SUMX(salary_data,(salary_data[Salary] - __muY) ^ 2)
                   )
 
RETURN
DIVIDE(__num, __denum)
  

Breaking Down the DAX Measure

VAR __muX = CALCULATE(AVERAGE(salary_data[YearsExperience] ))
VAR __muY = CALCULATE(AVERAGE(salary_data[Salary]))
  

🔹 This calculates the mean (average) values for the X and Y axes.

VAR __num = SUMX(salary_data,(salary_data[YearsExperience] - __muX) * (salary_data[Salary] - __muY))
  

🔹 This calculates the numerator: the sum of the products of the differences between each X and Y value from their means.

VAR __denum = SQRT(SUMX(salary_data,(salary_data[YearsExperience]- __muX) ^ 2) *
                   SUMX(salary_data,(salary_data[Salary] - __muY) ^ 2)
                   )
  

🔹 This calculates the denominator: the square root of the product of the sum of squared differences for both variables.

RETURN DIVIDE(__num, __denum)
  

🔹 Finally, the R² value is computed by dividing the numerator by the denominator.

Customizing the Measure

• 📌 Replace salary_data with your dataset’s name.
• 📌 Update YearsExperience and Salary to your X and Y axis fields.

Final Thoughts

By using this DAX measure, you can add an R² value to Power BI scatter plots, filling a critical gap in the built-in trend line feature. This helps in better understanding correlations and enhancing data-driven decision-making.

If you regularly work with regression analysis or data visualization, incorporating R-squared into your reports will add more credibility and depth to your insights.

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Download Example PBIX file

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