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Statistical Methods in Analytical Chemistry

Author : Peter C. Meier
Publisher : John Wiley & Sons
Page : 452 pages
File Size : 31,43 MB
Release : 2005-03-04
Category : Science
ISBN : 0471726117

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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

Data Analysis Techniques for Physical Scientists

Author : Claude A. Pruneau
Publisher : Cambridge University Press
Page : 719 pages
File Size : 26,93 MB
Release : 2017-10-05
Category : Science
ISBN : 1108267882

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A comprehensive guide to data analysis techniques for physical scientists, providing a valuable resource for advanced undergraduate and graduate students, as well as seasoned researchers. The book begins with an extensive discussion of the foundational concepts and methods of probability and statistics under both the frequentist and Bayesian interpretations of probability. It next presents basic concepts and techniques used for measurements of particle production cross-sections, correlation functions, and particle identification. Much attention is devoted to notions of statistical and systematic errors, beginning with intuitive discussions and progressively introducing the more formal concepts of confidence intervals, credible range, and hypothesis testing. The book also includes an in-depth discussion of the methods used to unfold or correct data for instrumental effects associated with measurement and process noise as well as particle and event losses, before ending with a presentation of elementary Monte Carlo techniques.

Statistical Methods of Analysis

Author : Chin Long Chiang
Publisher : World Scientific
Page : 660 pages
File Size : 21,7 MB
Release : 2003
Category : Business & Economics
ISBN : 9789812383105

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This textbook is related to a course that the author taught for many years at University of California, Berkeley. The course was originally intended for graduate students in the biological and health sciences. But it attracted students from other departments on the campus as well. In order for the book to serve the interest of a larger audience, the author made revisions of the outline, added new topics, and provided more examples for illustrations wherever needed. This invaluable book systematically presents fundamental methods of statistical analysis: from basic probability and statistical distributions, through fundamental concepts of statistical inference, to a collection of methods of analysis useful for scientific research. The text is rich in tables, diagrams, and examples, in addition to theoretical justification of the methods of analysis introduced. Each chapter has a section entitled "Exercises and Problems, " to accompaning the text. There are altogether about 300 exercises, whoseanswers are given. A section entitled "Proof of the Results in This Chapter" in each chapter provides interested readers with material for further study.

Analytical Methods in Statistics

Author : Matúš Maciak
Publisher : Springer Nature
Page : 159 pages
File Size : 25,44 MB
Release : 2020-07-19
Category : Mathematics
ISBN : 3030488144

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This book collects peer-reviewed contributions on modern statistical methods and topics, stemming from the third workshop on Analytical Methods in Statistics, AMISTAT 2019, held in Liberec, Czech Republic, on September 16-19, 2019. Real-life problems demand statistical solutions, which in turn require new and profound mathematical methods. As such, the book is not only a collection of solved problems but also a source of new methods and their practical extensions. The authoritative contributions focus on analytical methods in statistics, asymptotics, estimation and Fisher information, robustness, stochastic models and inequalities, and other related fields; further, they address e.g. average autoregression quantiles, neural networks, weighted empirical minimum distance estimators, implied volatility surface estimation, the Grenander estimator, non-Gaussian component analysis, meta learning, and high-dimensional errors-in-variables models.

Analytical Methods in Statistics

Author : Jaromír Antoch
Publisher : Springer
Page : 214 pages
File Size : 49,92 MB
Release : 2017-01-24
Category : Mathematics
ISBN : 3319513133

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This volume collects authoritative contributions on analytical methods and mathematical statistics. The methods presented include resampling techniques; the minimization of divergence; estimation theory and regression, eventually under shape or other constraints or long memory; and iterative approximations when the optimal solution is difficult to achieve. It also investigates probability distributions with respect to their stability, heavy-tailness, Fisher information and other aspects, both asymptotically and non-asymptotically. The book not only presents the latest mathematical and statistical methods and their extensions, but also offers solutions to real-world problems including option pricing. The selected, peer-reviewed contributions were originally presented at the workshop on Analytical Methods in Statistics, AMISTAT 2015, held in Prague, Czech Republic, November 10-13, 2015.

Statistics and Analysis of Scientific Data

Author : Massimiliano Bonamente
Publisher : Springer
Page : 323 pages
File Size : 44,16 MB
Release : 2016-11-08
Category : Science
ISBN : 1493965727

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The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: • a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. • a new chapter on the various measures of the mean including logarithmic averages. • new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. • a new case study and additional worked examples. • mathematical derivations and theoretical background material have been appropriately marked, to improve the readability of the text. • end-of-chapter summary boxes, for easy reference. As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.

Analytical Methods in Statistics

Author : Douglas Romero
Publisher : Createspace Independent Publishing Platform
Page : 210 pages
File Size : 50,21 MB
Release : 2017-10-10
Category :
ISBN : 9781985181267

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This book provides a compact self-contained introduction to the Analytical Methods in Statistics. The book is accessible to readers having a basic familiarity with probability, yet allows more advanced readers to quickly grasp the principles underlying Statistics theory and methods. The examples and computer code allow the reader to understand and implement basic Statistics data analyses using standard statistical models and to extend the standard models to specialized data analysis situations.

Statistical Treatment of Analytical Data

Author : Zeev B. Alfassi
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 28,45 MB
Release : 2009-02-12
Category : Science
ISBN : 1405148144

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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.

Analytic Methods in Sports

Author : Thomas A. Severini
Publisher : CRC Press
Page : 327 pages
File Size : 35,73 MB
Release : 2020-04-15
Category : Mathematics
ISBN : 1000050947

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One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter. Features Covers numerous statistical procedures for analyzing data based on sports results Presents fundamental methods for describing and summarizing data Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data Explains the statistical reasoning underlying the methods Illustrates the methods using real data drawn from a wide variety of sports Offers many of the datasets on the author’s website, enabling you to replicate the analyses or conduct related analyses New to the Second Edition R code included for all calculations A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more Exercises added to the end of each chapter, to enable use for courses and self-study