Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting

Description

Nonlinear regression is an essential tool for analyzing biological data, and is the most frequently used tool for data analysis in many labs. This book is written for biologists, not mathematical statisticians, and presents a practical approach to fitting curves with nonlinear regression. It explains how to choose a model, how to make sensible choices when using a nonlinear regression program, and how to interpret the results. It also helps you troubleshoot "bad" fits and explains how to compare models and data sets. In addition to general information about curve fitting, it also contains specific details about fitting radioligand binding, dose-response, and enzyme kinetic data, emphasizing the use of global regression. The last portion of the book explains how to fit curves with the program GraphPad Prism, but the book will be useful no matter what program you use.

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