How do you describe an analytical method, measure the purity of the new chemical that you have just synthesized, or report the proper units of measurement? For analytical chemists, the principal tool of the trade, or source of terms, is this book - the so-called Orange Book. First published in 1978, this latest edition takes into account the explosion of new analytical procedures and, at the same time, the diversity of techniques and the quality and performance characteristics of the procedures that are the focus of interest. The scope of analytical chemistry has widened, new types of instrumental techniques have emerged and automation has taken over. Answers can now be shared, not only on the chemical composition and structure of the sample, but also changes in composition and structure in space and time. New chapters on chemometrics, bio-analytical methods of analysis, and sample treatment and preparation have been added. The terminology of metrology and quality assurance is now up to date with the latest ISO and JCGM standards. This new volume will be an indispensable reference resource for the coming decade, revising and updating accepted terminology, and providing the official language of analytical chemistry.

Chemical data analysis, with aspects of metrology in chemistry and chemometrics, is an evolving discipline where new and better ways of doing things are constantly being developed. This book makes data analysis simple by demystifying the language and whenever possible giving unambiguous ways of doing things.
Based on author D. Brynn Hibberts lectures on data analysis to undergraduates and graduate students, Data Analysis for Chemistry
covers topics including measurements, means and confidence intervals, hypothesis testing, analysis of variance, and calibration models. The end result is a compromise between recipes of how to perform different aspects of data analysis, and basic information on the background principles behind the recipes to be performed. An entry level book targeted at learning and teaching undergraduate data analysis, Data Analysis for Chemistry makes it easy for readers to find the information they are seeking to perform the data analysis they think they need.

Analytical chemical results touch everyones lives can we eat the food? do I have a disease? did the defendant leave his DNA at the crime scene? should I invest in that gold mine? When a chemist measures something how do we know that the result is appropriate? What is fit for purpose in the context of analytical chemistry? Many manufacturing and service companies have embraced traditional statistical approaches to quality assurance, and these have been adopted by analytical chemistry laboratories. However the right chemical answer is never known, so there is not a direct parallel with the manufacture of ball bearings which can be measured and assessed. The customer of the analytical services relies on the quality assurance and quality control procedures adopted by the laboratory. It is the totality of the QA effort, perhaps first brought together in this text, that gives the customer confidence in the result. QA in the Analytical Chemistry Laboratory takes the reader through all aspects of QA, from the statistical basics and quality control tools to becoming accredited to international standards. The latest understanding of concepts such as measurement uncertainty and metrological traceability are explained for a working chemist or her client. How to design experiments to optimize an analytical process is included, together with the necessary statistics to analyze the results. All numerical manipulation and examples are given as Microsoft Excel spreadsheets that can be implemented on any personal computer. Different kinds of interlaboratory studies are explained, and how a laboratory is judged in proficiency testing schemes is described. Accreditation to ISO 17025 or OECD GLP is nearly obligatory for laboratories of any pretension to quality. Here the reader will find an introduction to the requirements and philosophy of accreditation. Whether completing a degree course in chemistry or working in a busy analytical laboratory, this book is a single source for an introduction into quality assurance.

Chemical data analysis, with aspects of metrology in chemistry and chemometrics, is an evolving discipline where new and better ways of doing things are constantly being developed. This book makes data analysis simple by demystifying the language and whenever possible giving unambiguous ways of doing things.
Based on author D. Brynn Hibberts lectures on data analysis to undergraduates and graduate students, Data Analysis for Chemistry covers topics including measurements, means and confidence intervals, hypothesis testing, analysis of variance, and calibration models. The end result is a compromise between recipes of how to perform different aspects of data analysis, and basic information on the background principles behind the recipes to be performed. An entry level book targeted at learning and teaching undergraduate data analysis, Data Analysis for Chemistry makes it easy for readers to find the information they are seeking to perform the data analysis they think they need.