Errorsmeasurement And Results In Chemical Analysis

It is now becoming recognized in the measurement community that it is as important to communicate the uncertainty related to a specific measurement as it is to report the measurement itself. Without knowing the uncertainty, it is impossible for the users of the result to know what confidence can be placed in it; it is also impossible to assess the comparability of different measurements of the same parameter. This volume collects 20 outstanding papers on the topic, mostly published from 1999-2002 in the journal "Accreditation and Quality Assurance." They provide the rationale for why it is important to evaluate and report the uncertainty of a result in a consistent manner. They also describe the concept of uncertainty, the methodology for evaluating uncertainty, and the advantages of using suitable reference materials. Finally, the benefits to both the analytical laboratory and the user of the results are considered.

The Application of Mathematical Statistics to Chemical Analysis presents the methods of mathematical statistics as applied to problems connected with chemical analysis. This book is divided into nine chapters that particularly consider the principal theorems of mathematical statistics that are explained with examples taken from researchers associated with chemical analysis in laboratory work. This text deals first with the problems of mathematical statistics as a means to summarize information in chemical analysis. The next chapters examine the classification of errors, random variables and their characteristics, and the normal distribution in mathematical statistics. These topics are followed by surveys of the application of Poisson's and binomial distribution in radiochemical analysis; the estimation of chemical analytic results; and the principles and application of determination of experimental variance. The last chapters explore the determination of statistical parameters of linear relations and some working methods associated with the statistical design of an experiment. This book will be of great value to analytical chemists and mathematical statisticians.

B. Sc. (Hons.) and M. Sc. classes of All Indian Universities [Also useful for Net Examination]

This definitive new book should appeal to everyone who produces, uses, or evaluates scientific data. Ensures accuracy and reliability. Dr. Taylor's book provides guidance for the development and implementation of a credible quality assurance program, plus it also provides chemists and clinical chemists, medical and chemical researchers, and all scientists and managers the ideal means to ensure accurate and reliable work. Chapters are presented in a logical progression, starting with the concept of quality assurance, principles of good measurement, principles of quality assurance, and evaluation of measurement quality. Each chapter has a degree of independence so that it may be consulted separately from the others.