The Application Of Mathematical Statistics To Chemical Analysis

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.

At a time when computerized laboratory automation is producing a da ta explosion, chemists are turning to applied mathematics and statistics for the tools to extract useful chemical information from data. This rush to find applicable methods has lead to a somewhat confusing body of literature that represents a barrier to chemists wishing to learn more about chemometrics. The confusion results partly from the mixing of chemical notation and nomenclature with those of statistics, applied mathematics and engineering. Additionally, in the absence of collaboration with mathematicians, chemists have, at times, misused data analysis methodology and even reinvented methods that have seen years of service in other fields. The Chemometrics Society has worked hard to solve this problem since it was founded in 1974 with the goal of improving communications between the chemical sciences and applied mathe matics and statistics. The NATO Advanced Study Institute on Chemometrics is evidence of this fact as it was initiated in response to a call from its membership for advanced training in several areas of chemometrics. This Institute focused on current theory and application in the new field of Chemometrics: Use of mathematical and statistical methods, Ca) to design or select optimal measurement procedures and experiments; and Cb) to provide maximum chemical information by analyzing chemical data. The Institute had two formal themes and two informal themes.

Chemometrics Explore chemometrics from basic statistics to the latest artificial intelligence and neural network developments in this new edition Chemometrics is an area of study combining chemistry and mathematics. It governs the interpretation of data generated by chemical analysis, and its growth as a subfield promises to streamline and revolutionize analytical chemistry. Chemometrics has long been the leading introductory textbook in this subject. Beginning with an introduction to the statistical-mathematical evaluation of chemical measurements, it leads readers through modern chemometric approaches in a pedagogically sound and highly readable style. Now fully updated to reflect the latest research and applications of this exciting discipline, it provides essential tools for a new generation of analytical chemists. Readers of the fourth edition of Chemometrics will also find: New or expanded treatment of subjects such as deep learning, ANNOVA simultaneous component analysis, instrumental data output, and more Detailed discussion of approaches to signal processing, design and optimization of experiments, pattern recognition and classification, and many other areas Balance of theoretical and practical knowledge to enable rapid application of key techniques Chemometrics is ideal for advanced students in chemistry, analytical chemistry, pharmaceutical chemistry, biochemistry, or related subjects, and as a useful reference for practicing researchers and laboratory professionals.

Approximately 1,000 problems — with answers and solutions included at the back of the book — illustrate such topics as random events, random variables, limit theorems, Markov processes, and much more.

This book is intended to help analytical chemists feel comfortable with more commonly used statistical operations and help them make effective use of the results. Emphasis is put upon computer-based methods that are applied in relation to measurement and the quality of the resulting data. The book is intended for analytical chemists working in industry but is also appropriate for students taking first degrees or an MSc in analytical chemistry. The authors have divided this book into quite short sections, each dealing with a single topic. The sections are as far as possible selfcontained, but are extensively cross-referenced. The book can therefore be used either systematically by reading the sections sequentially, or as a quick reference by going directly to the topic of interest. Every statistical method and application covered has at least one example where the results are analysed in detail. This enables readers to emulate this analysis on their own examples. All of the datasets used in examples are available for download, so that readers can compare their own output with that of the book and thus verify that they are entering data correctly into the statistical package that they happen to use. Contents:Statistics:PreliminariesThinking About Probabilities and DistributionsSimple Tests SignificanceAnalysis of Variance (ANOVA) and Its ApplicationsRegression and CalibrationRegression — More Complex AspectsAdditional Statistical TopicsData Quality in Analytical Measurement:Quality in Chemical MeasurementStatistical Methods Involved in ValidationInternal Quality ControlProficiency TestingSampling in Chemical Measurement Readership: Analytical chemists working in industry, students taking first degrees or an MSc in analytical chemistry. Keywords:Statistics;Data Quality;Analytical Chemistry;Analytical Sciences;Chemical Measurement;Uncertainty;Estimation;InferenceKey Features:The lead author chairs the Statistical Subcommittee in the Royal Society of Chemistry, UK, and has many years of experience teaching statistics to analytical chemists and knows where they have difficultyThere is a strong emphasis on the use of computers and graphical interpretation of dataReviews:“The book is a good description of basic statistical techniques for analytical chemists. There are a number of well established competitors on the market, however this book is definitely useful for a well stocked teaching lab and as reference for practicing analysts.”Chemistry World