This hands-on guide is primarily intended to be used in undergraduate laboratories in the physical sciences and engineering. It assumes no prior knowledge of statistics. It introduces the necessary concepts where needed, with key points illustrated with worked examples and graphic illustrations. In contrast to traditional mathematical treatments it uses a combination of spreadsheet and calculus-based approaches, suitable as a quick and easy on-the-spot reference. The emphasis throughout is on practical strategies to be adopted in the laboratory. Error analysis is introduced at a level accessible to school leavers, and carried through to research level. Error calculation and propagation is presented though a series of rules-of-thumb, look-up tables and approaches amenable to computer analysis. The general approach uses the chi-square statistic extensively. Particular attention is given to hypothesis testing and extraction of parameters and their uncertainties by fitting mathematical models to experimental data. Routines implemented by most contemporary data analysis packages are analysed and explained. The book finishes with a discussion of advanced fitting strategies and an introduction to Bayesian analysis.
Problems after each chapter
This book fulfills the global need to evaluate measurement results along with the associated uncertainty.
This guide is also useful to professionals in industry who are expected to know the contemporary methods in this increasingly important area. Additional online resources are available to support the book at www.cambridge.org/9780521605793.
Building on the fundamentals of measurement theory, this book offers a wealth of practial recommendations and procedures.
All formulations are discussed and demonstrated with the minimum of mathematical knowledge assumed. This second edition offers additional examples in each chapter, and detailed additions and alterations made to the text.
This book is mainly addressed to - dergraduate students, but can be a useful reference for researchers and for secondary school teachers. The book is divided into three parts and a series of appendices.
This book describes the methods and application of uncertainty analysis during the planning, data analysis, and reporting stages of an experiment.
Accred Qual Assur 14(2009), 159–166. 55 Burdick RK, Borror CM, Montgomery DC, Design and Analysis of Gauge R&R Studies. SIAM, 2005. 56 Montgomery DC, Runger GC, “Gauge capability and designed experiments, Part 1: Basic methods”,.
An overview of experimental methods providing practical advice to students seeking guidance with their experimental work.
NIST initially published a Technical Note on this issue in Jan. 1993. This 1994 edition addresses the most important questions raised by recipients concerning some of the points it addressed and some it did not. Illustrations.