Statistical Methods in Analytical Chemistry, 2nd edition

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Statistical Methods in Analytical Chemistry, 2nd edition

Peter C. Meier Richard E. Zünd
Statistical Methods in Analytical Chemistry, 2nd edition
Wiley-Interscience | ISBN: 0471293636 | 2000 | 456 pages | PDF | 20.0 MB

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.