Statistical Methods in Analytical Chemistry / Edition 2

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This book provides 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." "Statistical Methods in Analytical Chemistry, Second Edition is a 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.
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Editorial Reviews

SciTech Book
Substantially updated...this reference is intended for lab supervisors and project mangers, and is useful...for advanced students of chemistry and pharmaceutical science.
SciTech Book
Substantially updated...this reference is intended for lab supervisors and project mangers, and is useful...for advanced students of chemistry and pharmaceutical science.
Annali di Chimica
...a comprehensive, very useful and clear guide for all analytical chemists...
SciTech Book News
Substantially updated...for lab supervisors and project mangers, and is useful...for advanced students of chemistry and pharmaceutical science.
Substantially updated since its first version published in the late 1980s, this reference is intended for lab supervisors and project managers, and is useful as well for advanced students of chemistry and pharmaceutical science. It focuses on the complete data evaluation cycle<-->question, plan, experiment, result, interpretation, and answer. Though the case studies involve quality control in the chemical and pharmaceutical industries, the general principles apply to chemical analysis in any industrial setting. Coverage includes univariate, bivariate, and multivariate data, and ancillary techniques<-->optimization, exploratory data analysis, smoothing and computer simulation, and recapitulation of error propagation. The authors are analytical chemists in the pharmaceutical industry. Annotation c. Book News, Inc., Portland, OR (
From the Publisher

“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.” (PDFCHM Online, 27 February 2013)

"...a comprehensive, very useful and clear guide for all analytical chemists..." (Annali di Chimica, Vol 153, 2000)

"Substantially updated...for lab supervisors and project mangers, and is useful...for advanced students of chemistry and pharmaceutical science." (SciTech Book News, Vol. 24, No. 2, June 2001)

"Its clarity, focus and logical approach to statistical analysis of chemical data make it a book that should appear on the bookshelf of most analytical chemists." (Journal of the American Chemical Society, Vol. 123 No. 36)

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Product Details

Meet the Author

PETER C. MEIER, PhD, currently serves as Director for the Cilag A.G., a member of the Johnson & Johnson Company, and as a faculty member for the Swiss Federal Institute of Technology in Zurich (ETH-Z). The author/coauthor of 27 publications, Dr. Meier has held managerial positions in both Quality Assurance and pharmaceutical R&D, sat on the board of the former Swiss Society for Instrumental Analysis, and for many years was a member of Analytica Chimica Acta's Advisory Board.

RICHARD E. ZUND, PhD, has been with Teranol A.G., a member of the Roche Group, since 1995 and is currently responsible for Teranol's IPC/QC/QA section, which covers, among other things, equipment, methods, statistics, audits, and specifications. Dr. Zund is a member of Roche's Divisional QA and GMP Expert Team for the Vitamins and Fine Chemicals Sector. He previously headed the QA-IPC section and was strongly involved in ISO 9001 and LIMS projects, among other functions.

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Table of Contents

Chemical Analysis Series
Introduction 1
Ch. 1 Univariate Data 13
1.1 Mean and Standard Deviation 13
1.2 Distributions and the Problem of Small Numbers 29
1.3 Confidence Limits 35
1.4 The Simulation of a Series of Measurements 41
1.5 Testing for Deviations 44
1.6 Number of Determinations 65
1.7 Width of a Distribution 69
1.8 Charting a Distribution 74
1.9 Errors of the First and Second Kind 87
Ch. 2 Bi- and Multivariate Data 91
2.1 Correlation 92
2.2 Linear Regression 94
2.3 Nonlinear Regression 127
2.4 Multidimensional Data/Visualizing Data 132
Ch. 3 Related Topics 137
3.1 GMP Background: Selectivity and Interference/Linearity/Accuracy/Precision/Reliability/Economic Considerations 137
3.2 Development, Qualification, and Validation; Installation Qualification, Operations Qualification, Performance Qualification/Method Development/Method Validation 140
3.3 Data Treatment Scheme: Data Acquisition/Acceptance Criteria/Data Assembly and Clean-up/Data Evaluation/Presentation of Results/Specifications/Records Retention 145
3.4 Exploratory Data Analysis (EDA) 148
3.5 Optimization Techniques 149
3.6 Smoothing and Filtering Data/Box-Car Averaging/Moving Average/Savitzky-Golay Filtering/CUSUM 167
3.7 Error Propagation and Numerical Artifacts 169
3.8 Programs 171
Ch. 4 Complex Examples 175
4.1 To Weight or Not to Weigh 175
4.2 Nonlinear Fitting 180
4.3 UV-Assay Cost Structure 185
4.4 Process Validation 190
4.5 Regulations and Realities 193
4.6 Diffusing Vapors 199
4.7 Stability a la Carte 202
4.8 Secret Shampoo Switch 203
4.9 Tablet Press Woes 205
4.10 Sounding Out Solubility 208
4.11 Exploring a Data Jungle 210
4.12 Sifting Through Sieved Samples 215
4.13 Controlling Cyanide 221
4.14 Ambiguous Automation 225
4.15 Mistrusted Method 229
4.16 Quirks of Quantitation 230
4.17 Pursuing Propagating Errors 235
4.18 Content Uniformity 237
4.19 How Full Is Full? 240
4.20 Warranty or Waste 245
4.21 Arrhenius-Abiding Aging 249
4.22 Facts of Artifacts? 251
4.23 Proving Proficiency 254
4.24 Gotta Go Gambling 263
4.25 Does More Sensitivity Make Sense? 277
4.26 Pull the Brakes! 279
4.27 The Limits of Nonlinearities 280
4.28 The Zealous Statistical Apprentice 283
4.29 Not Perfect, but Workable 288
4.30 Complacent Control 291
4.31 Spring Cleaning 295
4.32 It's All a Question of Pedigree 304
4.33 New Technology Rattles Old Dreams 308
4.34 Systems Suitability 310
4.35 An Eye Opener 311
4.36 Boring Bliss 313
4.37 Keeping Track of Dissolving Tablets 317
4.38 Poking Around in the Fog 319
Ch. 5 Appendices 329
5.1 Numerical Approximations to Some Frequently Used Distributions 329
5.2 Core Instructions Used in Several Programs 339
5.3 Installation and Use of Programs on Diskette 339
5.4 Program and Data File Description 361
Technical Tidbits 399
Glossary 401
References 404
Index 417
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