Statistical Analysis Methods For Chemists

Many forms of chemical experimentation generate data needing analysis and interpretation in respect of the goals of the experiment and also the chemical factors which may influence the outcome. Statistical data analysis techniques provide the tools which enable a chemist to assess the information obtained from experiments. Statistical Analysis Methods for Chemists: A Software-based Approach aims to give a broad introduction to practical data analysis, and provides comprehensive coverage of basic statistical principles and reasoning. With practical examples, and integration of software output as the basis of data analysis, this useful book gives unique coverage of the statistical skills and techniques required in modern chemical experimentation. It will prove invaluable to students and researchers alike. Software update information is available from W Gardiner at [email protected] or fax +44 (0)141 331 3608. Please accompany requests for information with details of the software version to be used.

This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly demonstrates how to obtain reliable results by choosing the most appropriate experimental design and data evaluation methods. Unlike other books on the subject, Statistical Methods in Analytical Chemistry, Second Edition presents and solves problems in the context of a comprehensive decision-making process under GMP rules: Would you recommend the destruction of a $100,000 batch of product if one of four repeat determinations barely fails the specification limit? How would you prevent this from happening in the first place? Are you sure the calculator you are using is telling the truth? To help you control these situations, the new edition: * Covers univariate, bivariate, and multivariate data * Features case studies from the pharmaceutical and chemical industries demonstrating typical problems analysts encounter and the techniques used to solve them * Offers information on ancillary techniques, including a short introduction to optimization, exploratory data analysis, smoothing and computer simulation, and recapitulation of error propagation * Boasts numerous Excel files and compiled Visual Basic programs-no statistical table lookups required! * Uses Monte Carlo simulation to illustrate the variability inherent in statistically indistinguishable data sets Statistical Methods in Analytical Chemistry, Second Edition is an excellent, one-of-a-kind resource for laboratory scientists and engineers and project managers who need to assess data reliability; QC staff, regulators, and customers who want to frame realistic requirements and specifications; as well as educators looking for real-life experiments and advanced students in chemistry and pharmaceutical science. From the reviews of Statistical Methods in Analytical Chemistry, First Edition: "This book is extremely valuable. The authors supply many very useful programs along with their source code. Thus, the user can check the authenticity of the result and gain a greater understanding of the algorithm from the code. It should be on the bookshelf of every analytical chemist."-Applied Spectroscopy "The authors have compiled an interesting collection of data to illustrate the application of statistical methods . . . including calibrating, setting detection limits, analyzing ANOVA data, analyzing stability data, and determining the influence of error propagation."-Clinical Chemistry "The examples are taken from a chemical/pharmaceutical environment, but serve as convenient vehicles for the discussion of when to use which test, and how to make sense out of the results. While practical use of statistics is the major concern, it is put into perspective, and the reader is urged to use plausibility checks."-Journal of Chemical Education "The discussion of univariate statistical tests is one of the more thorough I have seen in this type of book . . . The treatment of linear regression is also thorough, and a complete set of equations for uncertainty in the results is presented . . . The bibliography is extensive and will serve as a valuable resource for those seeking more information on virtually any topic covered in the book."-Journal of American Chemical Society "This book treats the application of statistics to analytical chemistry in a very practical manner. [It] integrates PC computing power, testing programs, and analytical know-how in the context of good manufacturing practice/good laboratory practice (GMP/GLP) . . .The book is of value in many fields of analytical chemistry and should be available in all relevant libraries."-Chemometrics and Intelligent Laboratory Systems

Statistical techniques have assumed an integral role in both the interpretation and quality assessment of analytical results. In this book the range of statistical methods available for such tasks are described in detail, with the advantages and disadvantages of each technique clarified by use of examples. With a focus on the essential practical application of these techniques the book also includes sufficient theory to facilitate understanding of the statistical principles involved. Statistical Treatment of Analytical Data is written for professional analytical chemists in industry, government and research institutions who require a practical understanding of the application of statistics in day to day activities in the analytical laboratory. It is also for students who require further and detailed information that may not be available directly in a typical undergraduate course.

Provides a clear explanation of the underlying principles of traditional statistical methods and reflects the enormous impact of microelectronics for the rapid calculation of chemometric procedures. Text focuses on tests appropriate to the problems likely to be encountered in the laboratory. Provides full coverage of such topics as errors in classical analysis; significance tests; quality control and sampling; errors in instrument analysis; regression and correlation; rapid and non-parametric methods; experimental design, optimization, and pattern recognition. Helpful for students, technicians, and scientists in all areas of analytical chemistry and related fields.

This popular textbook gives a clear and lucid account of the underlying principles of statistical methods. The fourth edition has been revised and updated to reflect the growing popularity of statistics and chemometric methods and new approaches in optimization and experimental design. The authors have also addressed the quality of analytical chemistry data and experimental results, an area of increasing concern to chemists testing the safety of food and medicines. This book will suit undergraduate, M.Sc. and graduate courses in Analytical Chemistry and related topics, and will also be valuable for researchers and chemists working in analytical chemistry everywhere.

Annotation. Definitions, Questions, and Useful Functions: Where to Find Things and What To Do1. Introduction2. Describing Data3. Hypothesis Testing4. Analysis of Variance5. Calibration.

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.