Coefficient of Determination (R2) Calculator

Your details

Your independent (predictor) variable values. Separate them with commas, semicolons, or spaces. Must have at least 3 points.
Your dependent (response) variable values. Must have the same count as x values.
R2 (coefficient of determination)Very strong fit
0.9567

Proportion of variance in y explained by x (0 to 1)

Variance explained0.96%
Pearson r0.9781
Slope (b1)0.9214
Intercept (b0)0.7286
SSE (error)1.0757
SSR (regression)23.7729
SST (total)24.8486
n (data points)7
0.9567 R2
Very weak<0.25Weak0.25-0.5Moderate0.5-0.7Strong0.7-0.9Very strong0.9+

R2 = 0.9567: a very strong linear fit, explaining 95.7% of variance in y.

  • 95.7% of the variation in y is explained by the linear relationship with x; the remaining 4.3% is due to other factors or random noise.
  • The regression line is y = 0.9214x + 0.7286.
  • With 7 data points, the Pearson correlation r is 0.9781, indicating a very strong positive linear association.
  • An extremely high R2 can sometimes indicate overfitting or a spurious correlation; always check whether the relationship makes scientific or practical sense.

Next stepPlot your residuals to check the linearity assumption and look for outliers, then consider whether additional predictors could improve the model.

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