Fitting Models To Biological Data Using Linear And Nonlinear Regression: A Practical Guide To Curve Fitting

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

Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.From the Inside Flap"This well-written book fills a major need for biomedical researchers -- an explanation of nonlinear regression that is simple, deep, insightful and practical." Lee E. Limbird, Ph.D. Dept. Pharmacology Vanderbilt University"Because the data from many of the experiments in my laboratory are analyzed by curve fitting, it is important that my postdoctoral fellows, students and senior technicians understand the basic principles of nonlinear regression. But it has been hard for them to do so. Basic statistics books don't discuss curve fitting, advanced books on nonlinear regression tend to be too mathematical, and the manuals that come with computer programs tend to be too narrow. Motulsky and Christopolous do a excellent job of explaining the principles of curve fitting (with enough but not too much math) along with practical discussions of how to pick a model, how to make sense of results, what to do when the results appear to be nonsense and how to compare curves. I enthusiastically recommend this book to anyone doing research in pharmacology, biophysics or biochemistry -- especially for those generating dose-response, ligand binding or enzyme kinetic data (as these are discussed in detail). " David B. Bylund, Ph.D. Professor of Pharmacology University of Nebraska Medical CenterAbout the AuthorArthur Christopoulos is at University of Melbourne.