| General Introduction to Regression Analysis / Part I： |
| Introduction to Nonlinear Modeling of Data: What is Nonlinear Modeling? Objectives of this Book |
| Anayzing Data with Regression Analysis: Linear Models |
| Nonlinear Regression Analysis |
| Sources of Mathematics Software Capable of Linear and Nonlinear Regression |
| Building Models for Experimental Data: Sources of Data and Background Contributions |
| Examples of Model Types |
| Finding the Best Models |
| Correlation Between Parameters and Other Convergence Problems: Correlations and How to Minimize Them |
| Avoiding Pitfalls in Convergence |
| Selected Applications / Part II： |
| Titrations: Introduction |
| Macromolecular Equilibria and Kinetics: Linked Thermodynamic Models: The Concept of Linked Functions |
| Applications of Thermodynamic Linkage |
| Secondary Structure of Proteins by Infrared Spectroscopy: Introduction |
| Analysis of Spectra--Examples |
| Nuclear Magnetic Resonance Relaxation: Fundamentals of NMR Relaxation |
| Applications from NMR in Solution |
| Applications from NMR in the Solid State |
| Small-Angle X-Ray Scattering (SAXS) of Proteins: Theoretical Considerations |
| Applications |
| Ultracentrifugation of Macromolecules: Sedimentation |
| Voltammetric Methods: General Characteristics of Voltammetry |
| Steady State Voltammetry |
| Cyclic Voltammetry |
| Square Wave Voltammetry |
| Chronocoulometry: Basic Principles |
| Estimation of Diffusion Coefficients |
| Surface Concentrations of Adsorbates from Double Potential Steps |
| Rate Constant for Reaction of a Product of an Electrochemical Reaction |
| Automated Resolution of Multiexponential Decay Data: Considerations for Analyses of Overlapped Signals |
| Automated Analysis of Data with an Unknown Number of Exponentials |
| Chromatography and Multichannel Detection Methods: Overlapped Chromatographic Peaks with Single-Channel Detection |
| Multichannel Detection |
| Appendix |
| Subject Index |
| General Introduction to Regression Analysis / Part I： |
| Introduction to Nonlinear Modeling of Data: What is Nonlinear Modeling? Objectives of this Book |
| Anayzing Data with Regression Analysis: Linear Models |
図書
