Polynomial Regression Calculator

Your details

Enter one x,y pair per line. Separate x and y with a comma, space, or tab. At least (degree + 1) valid pairs are required.
Degree 1 is a straight line; degree 2 is a parabola. Higher degrees fit more complex curves but can overfit small datasets.
Controls how many decimal places are shown in coefficients and results.
Enter any x-value to interpolate or extrapolate a predicted y from the fitted polynomial.
Fitted equation
y = 1.0488x^2 - 0.5012x + 1.5286

The polynomial equation with computed coefficients

R-squared (R²)0.9997
Adjusted R-squared0.9996
RMSE0.2717
Data points used7
Predicted y64.6429

Fit quality is excellent (R-squared above 0.99).

  • The degree-2 polynomial explains 100.0% of the variation in your y-values.
  • Adjusted R-squared is 0.9996, which penalises extra coefficients and is better for comparing models of different degrees.
  • RMSE of 0.2717 is the typical distance (in y-units) between your data and the fitted curve.

Next stepCompare R-squared and adjusted R-squared across degrees: if adjusted R-squared stops increasing or decreases, the current degree is likely sufficient.

 = Powered by OnlyCalculators