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Fitting models to biological data using linear and nonlinear regression : a practical guide to curve fitting / by Harvey Motulsky, Arthur Christopoulos.

By: Motulsky, HarveyContributor(s): Christopoulos, ArthurMaterial type: TextTextPublication details: Oxford ; New York : Oxford University Press, 2004. Description: 1 online resource (351 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9780198038344; 0198038348; 9786610843770; 6610843775Subject(s): Biology -- Mathematical models | Regression analysis | Nonlinear theories | Curve fitting | Models, Biological | Regression Analysis | Nonlinear Dynamics | Biologie -- Modèles mathématiques | Analyse de régression | Théories non linéaires | Ajustement de courbe | NATURE -- Reference | SCIENCE -- Life Sciences -- Biology | SCIENCE -- Life Sciences -- General | Biology -- Mathematical models | Curve fitting | Nonlinear theories | Regression analysis | Biologie | Biostatistik | Experimentauswertung | Lineare Regression | Nichtlineare RegressionGenre/Form: Electronic books. | Electronic books. Additional physical formats: Print version:: Fitting models to biological data using linear and nonlinear regression.DDC classification: 570/.1/5118 LOC classification: QH323.5 | .M68 2003ebOther classification: WC 7000 | BIO 110f | MAT 628f Online resources: Click here to access online
Contents:
Contents; Preface; A. Fitting data with nonlinear regression; B. Fitting data with linear regression; C. Models; D. How nonlinear regression works; E. Confidence intervals of the parameters; F. Comparing models; G. How does a treatment change the curve?; H. Fitting radioligand and enzyme kinetics data; I. Fitting dose-response curves; J. Fitting curves with GraphPad Prism; Annotated bibliography; Index.
Summary: Fitting data with nonlinear regression. 1. An example of nonlinear regression. 2. Preparing data for nonlinear regression. 3. Nonlinear regression choices. 4. The first five questions to ask about nonlinear regression results. 5. The results of nonlinear regression. 6. Troubleshooting "bad fits". Fitting data with linear regression. 7. Choosing linear regression. 8. Interpreting the results of linear regression. Models. 9. Introducing models. 10. Tips on choosing a model. 11. Global models. 12. Compartmental models and defining a model with a differential equation. How nonlinear regr.
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Includes bibliographical references and index.

Contents; Preface; A. Fitting data with nonlinear regression; B. Fitting data with linear regression; C. Models; D. How nonlinear regression works; E. Confidence intervals of the parameters; F. Comparing models; G. How does a treatment change the curve?; H. Fitting radioligand and enzyme kinetics data; I. Fitting dose-response curves; J. Fitting curves with GraphPad Prism; Annotated bibliography; Index.

Fitting data with nonlinear regression. 1. An example of nonlinear regression. 2. Preparing data for nonlinear regression. 3. Nonlinear regression choices. 4. The first five questions to ask about nonlinear regression results. 5. The results of nonlinear regression. 6. Troubleshooting "bad fits". Fitting data with linear regression. 7. Choosing linear regression. 8. Interpreting the results of linear regression. Models. 9. Introducing models. 10. Tips on choosing a model. 11. Global models. 12. Compartmental models and defining a model with a differential equation. How nonlinear regr.

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