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 |