#### Nonlinear Regression: Summary

##### Key points from this module:

- Nonlinear regression minimizes the sum of the squares of the residuals; the residuals are the differences between the measured value and the value predicted by the model.
- In general, nonlinear regression is preferred over linear regression.
- When parameters are determined by nonlinear regression, their confidence limits must be determined in order to determine how close the measured values are to the true values.

##### From studying this module, you should now be able to:

- Apply nonlinear regression to obtain values of parameters and their 95% confidence intervals.

See the Virtual Catalytic Reactor Laboratory

*Prepared by John L. Falconer, Department of Chemical and Biological Engineering, University of Colorado Boulder*