Calibration Curve is a mathematical relationship between the instrument response and the known concentration or property value of calibration standards — typically a plot of signal (intensity, counts, absorbance) vs. known value, fitted with a regression model to convert measured signals into quantitative results.

Calibration Curve Construction

• Standards: Prepare 5-7+ calibration standards spanning the expected measurement range — plus a blank (zero standard).
• Measurement: Measure each standard — record the instrument response (signal).
• Regression: Fit a model (linear, quadratic, or weighted) to the signal vs. concentration data.
• R²: Correlation coefficient should be >0.999 for linear calibration — indicates good fit.

Why It Matters

• Quantification: The calibration curve converts raw instrument signals into meaningful concentration values — the basis of quantitative analysis.
• Range: The calibration curve defines the valid measurement range — extrapolation beyond the curve is unreliable.
• Frequency: Calibration curves should be refreshed regularly or verified — instrument drift changes the curve.

Calibration Curve is the translator from signals to numbers — the mathematical relationship that converts raw instrument responses into quantitative measurements.