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Data analysis is important from two points of view: first, it enables a large mass of information to be reduced to a reasonable compass, and second, it assists in the interpretation of experimental results against some framework of theory. The purpose of this text is to provide a practical introduction to numerical methods of data analysis which have applica tion in the field of experimental chemical kinetics. Recognizing that kinetic data have many features in common with data derived from other sources, I have considered it appropriate to discuss a selection of general methods of data analysis in the early chapters of the text. It is the author's experience that an outline of these methods is not always easy to locate in summary form, and that their usefulness is often not sufficiently appreciated. Inclusion of these methods in the early chapters has been aimed at simplifying discussion in the later chapters which are more particularly concerned with kinetic systems. By the provision of a number of worked examples and problems, it is hoped that the reader will develop a feeling for the range of methods available and for their relative merits. Throughout the text, the mathematical treatment has been kept relatively simple, lengthy proofs being avoided. I have preferred to indicate the 'sense' and usefulness of the various methods rather than to justify them on strict mathematical grounds.
Chemical processes in many fields of science and technology, including combustion, atmospheric chemistry, environmental modelling, process engineering, and systems biology, can be described by detailed reaction mechanisms consisting of numerous reaction steps. This book describes methods for the analysis of reaction mechanisms that are applicable in all these fields. Topics addressed include: how sensitivity and uncertainty analyses allow the calculation of the overall uncertainty of simulation results and the identification of the most important input parameters, the ways in which mechanisms can be reduced without losing important kinetic and dynamic detail, and the application of reduced models for more accurate engineering optimizations. This monograph is invaluable for researchers and engineers dealing with detailed reaction mechanisms, but is also useful for graduate students of related courses in chemistry, mechanical engineering, energy and environmental science and biology.
Kinetic models have often served as useful examples in develop ing the methodology for the design and analysis of experiments in volving mechanistic models. Thus, it is not surprising that these approaches have been applied quite successfully to kinetic obser vations. Nevertheless, many ideas and methods were developed indepen dently in various fields of science. More often than not, investi gators working in one area have not been aware of relevant advances in others. In order to facilitate the desirable exchange of ideas, a one-day symposium was held in Toronto in conjunction with the XIth International Congress of Biochemistry. Biochemists, pharmacolo gists,> and statisticians came together and discussed many of the topics presented in this volume. Participants in the symposium believed that it would be use ful to publish a collection of the presentations together with some additional material. The present volume is the result. It is an attempt to convey some of the interdisciplinary concerns involv ing mechanistic, and especially kinetic, model building. The coverage is by no means exhaustive: many principles, methods, and problems are not included. Even the applications are limited to biochemistry and pharmacology. Still, the symposium highlighted areas of current interest. These included questions of weighting, robust parameter estimation, pooled data analysis, model identification, and the design of experiments. These topics, which are of interest in many fields of science, are discus3ed also in the present volume.