Linear Regression and the Calibration Curve:

This section outlines the use of linear regression techniques and correlation coefficients in determining the calibration curve for a given instrument, method, sample, and analyte. This includes procedures for dealing with outliers in the calibration data, and for estimating the uncertainty associated with sample concentrations determined using the calibration curves. Examples of how to perform all of the required analyses in Excel™ are included throughout, and build on the previous exercises in the section on Excel™ Basics.

Tips & links:

Section Outline

Skip to Calibration Functions

Calibration Functions
→   Introduction to calibration curves and functions
The Correlation Coefficient
→   Definition and use of R, the product moment correlation coefficient
Linear portions of the curves
→   Using linear portion of curves for equation estimation
The Regression Equation
→   Calculation of a calibration curve using linear regression
Regression Errors
→   Estimating the errors in the regression, slope, and intercept
Using the Calibration
→   Estimating the uncertainties in concentrations obtained from the calibration curve
Limits of detection
→   Determining the limit of detection of an instrumental method
→   Evaluation of outliers with the Q-test and Grubbs test

Start with Calibration Functions...