This text, aimed at those who produce, use, or evaluate scientific data, provides guidance for the development and implementation of a credible quality assurance programme and the means to ensure accurate and reliable work. Chapters are presented in a logical progression, starting with the concept of quality assurance, principles of good measurement, principles of quality assurance, and evaluation of measurement quality. Each chapter has a degree of independence so that it may be consulted separately from the others.

Since the first edition of this book appeared, computers have come to the aid of modern experimenters and data analysts, bringing with them data analysis techniques that were once beyond the calculational reach of even professional statisticians. Today, scientists in every field have access to the techniques and technology they need to analyze statistical data. All they need is practical guidance on how to use them.
Valuable to everyone who produces, uses, or evaluates scientific data, Statistical Techniques for Data Analysis, Second Edition provides straightforward discussion of basic...