Linearity & Calibration Curve Calculator

Paste your calibration levels and get the regression, r² and back-calculated accuracy.

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Concentration and response, one level per line

Weighting

100% level (for intercept %)

Example: assay linearity from 10% to 150% of the target concentration. Paste from Excel with commas, tabs or spaces.

Slope–

Intercept–

r²–

Residual SD–

Intercept % of 100% response–

Weighted least squares: slope = (Σw·Σwxy − Σwx·Σwy)/(Σw·Σwx² − (Σwx)²) · %RE = (back-calculated − nominal)/nominal·100

How it works

ICH Q2(R2) asks for at least five concentration levels across the range, with the regression line, correlation coefficient, y-intercept and residual sum of squares reported. A high r² alone does not prove linearity: look at the residuals and the back-calculated accuracy at each level.

When the variance grows with concentration, as it usually does over the wide ranges of bioanalytical methods, weighted regression (1/x or 1/x²) stops the top standards dominating the fit and gives better accuracy at the low end. ICH M10 requires back-calculated standards within ±15% of nominal (±20% at the LLOQ).