All Shops

Go to British Wildlife

6 issues per year 84 pages per issue Subscription only

British Wildlife is the leading natural history magazine in the UK, providing essential reading for both enthusiast and professional naturalists and wildlife conservationists. Published six times a year, British Wildlife bridges the gap between popular writing and scientific literature through a combination of long-form articles, regular columns and reports, book reviews and letters.

Subscriptions from £25 per year

Conservation Land Management

4 issues per year 44 pages per issue Subscription only

Conservation Land Management (CLM) is a quarterly magazine that is widely regarded as essential reading for all who are involved in land management for nature conservation, across the British Isles. CLM includes long-form articles, events listings, publication reviews, new product information and updates, reports of conferences and letters.

Subscriptions from £18 per year
Academic & Professional Books  Reference  Data Analysis & Modelling  Bioinformatics

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

By: Harvey Motulsky and Arthur Christopoulos
351 pages, 150 illus
Fitting Models to Biological Data Using Linear and Nonlinear Regression
Click to have a closer look
Select version
  • Fitting Models to Biological Data Using Linear and Nonlinear Regression ISBN: 9780195171808 Paperback Jun 2004 Usually dispatched within 5 days
    £45.99
    #147528
  • Fitting Models to Biological Data Using Linear and Nonlinear Regression ISBN: 9780195171792 Hardback Feb 2004 Usually dispatched within 2-3 weeks
    £110.00
    #147529
Selected version: £45.99
About this book Contents Customer reviews Related titles

About this book

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 relavtively focused need of an extraordinarily broad range of scientists.

Contents

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 REGRESSION WORKS; 13. Modeling experimental error; 14. Unequal weighting of data points; 15. How nonlinear regression minimized the sum-of-squares; CONFIDENCE INTERVALS OF THE PARAMETERS; 16. Asymptotic standard errors and confidence intervals; 17. Generating confidence intervals by Monte Carlo simulations; 18. Generating confidence intervals via model comparison; 19. comparing the three methods for creating confidence intervals; 20. Using simulations to understand confidence intervals and plan experiments; COMPARING MODELS; 21. Approach to comparing models; 22. Comparing models using the extra sum-of-squares F test; 23. Comparing models using Akaike's Information Criterion; 24. How should you compare modes-AICe or F test?; 25. Examples of comparing the fit of two models to one data set; 26. Testing whether a parameter differs from a hypothetical value; HOW DOES A TREATMENT CHANGE THE CURVE?; 27. Using global fitting to test a treatment effect in one experiment; 28. Using two-way ANOVA to compare curves; 29. Using a paired t test to test for a treatment effect in a series of matched experiments; 30. Using global fitting to test for a treatment effect in a series of matched experiments; 31. Using an unpaired t test to test for a treatment effect in a series of unmatched experiments; 32. Using global fitting to test for a treatment effect in a series of unmatched experiments; FITTING RADIOLIGAND AND ENZYME KINETICS DATA; 33. The law of mass action; 34. Analyzing radioligand binding data; 35. Calculations with radioactivity; 36. Analyzing saturation radioligand binding data; 37. Analyzing competitive binding data; 38. Homologous competitive binding curves; 39. Analyzing kinetic binding data; 40. Analyzing enzyme kinetic data; FITTING DOES-RESPONSE CURVES; 41. Introduction to dose-response curves; 42. The operational model of agonist action; 43. Dose-response curves in the presence of antagonists; 44. Complex dose-response curves; FITTING CURVES WITH GRAPHPAD PRISM; 45. Nonlinear regression with Prism; 46. Constraining and sharing parameters; 47. Prsim's nonlinear regression dialog; 48. Classic nonlinear models built-in to Prism; 49. Importing equations and equation libraries; 50. Writing user-defined models in Prism; 51. Linear regression with Prism; 52. Reading unknowns from standard curves; 53. Graphing a family of theoretical curves; 54. Fitting curves without regression

Customer Reviews

By: Harvey Motulsky and Arthur Christopoulos
351 pages, 150 illus
Current promotions
Handbook of the mammals of the world batsJohns Hopkins University PressBritish WildlifeOrder your free copy of our 2018 equipment catalogue