Statistical
RSQ Function in Excel
Returns the square of the Pearson product moment correlation coefficient (R²).
Syntax
- =RSQ(known_y's, known_x's)
Arguments
- known_y's (required): Dependent values
- known_x's (required): Independent values
Examples
- =RSQ(B1:B10, A1:A10) - R-squared - Result: R² value
RSQ for data analysis
- Confirm whether you need entire columns, filtered subsets, or distinct values.
- Use [COUNTIFS](/functions/countifs/) and [SUMIFS](/functions/sumifs/) for multi-criteria metrics.
- Pivot tables complement single-cell statistical formulas for exploration.
Common errors
- Arrays must be same size
Use cases
- Regression quality
- Model fit
- Explained variance
Frequently asked questions
- What is RSQ (R-squared) in Excel? RSQ returns R², the coefficient of determination, which measures how well a regression line fits the data. It represents the proportion of variance in Y explained by X. R²=0.85 means 85% of Y's variation is explained by the linear relationship with X.
- How do I interpret R-squared values? R² ranges from 0 to 1. Higher is better: 0.9+ excellent fit, 0.7-0.9 good, 0.5-0.7 moderate, <0.5 weak. However, context matters - in social sciences 0.3 might be good; in physics 0.99 might be expected. Always consider the domain.
- What's the relationship between RSQ and PEARSON? RSQ = PEARSON² (correlation squared). If PEARSON returns 0.9, RSQ returns 0.81. RSQ loses the sign, so you can't tell if the relationship is positive or negative. Use PEARSON/CORREL to see direction, RSQ to see strength of fit.
Editorial review
- Reviewed by Excel.Directory Editorial Team. Updated May 2026.