This work details the fundamentals of applied statistics and experimental design, presenting a unified approach to data handling that emphasizes the analysis of variance, regression analysis and the use of Statistical Analysis System computer programs. This edition: discusses modern nonparametric methods; contains information on statistical process control and reliability; supplies fault and event trees; furnishes numerous additional end-of-chapter problems and worked examples; and more.
Thoroughly updated throughout, this second edition will continue to be about the practicable methods of statistical applications for engineers, and as well for scientists and those in business. It remains a what-I-wish-I-had-known-when-starting-my-career compilation of techniques. Contrasting a mathematical and abstract orientation of many statistics texts, which expresses the science/math values of researchers, this book has its focus on the application to concrete examples and the interpretation of outcomes. Supporting application propriety, this book also presents the fundamental concepts, provides supporting derivation, and has frequent do and not-do notes. Key Features: Contains details of the computation for the examples. Includes new examples and exercises. Includes expanded topics supporting data analysis. The book is for upper-level undergraduate or graduate students in engineering, the hard sciences, or business programs. The intent is that the text would continue to be useful in professional life, and appropriate as a self-learning tool after graduation – whether in graduate school or in professional practice.
Textbook on the understanding and application of statistical procedures to engineering problems, for practicing engineers who once had an introductory course in statistics, but haven't used the techniques in a long time; for statisticians and mathematicians now faced with the necessity of interactin
Practical and easy to use, this superbly illustrated text will provide the trainee with diagnostic and surgical guidance, tips and tricks, and a good solid background to the use of minimally invasive urological surgery techniques. The editors, all experts in urological laparoscopy, have chosen an elite team, mainly from the USA and Germany,
A guide to testing statistical hypotheses for readers familiar with the Neyman-Pearson theory of hypothesis testing including the notion of power, the general linear hypothesis (multiple regression) problem, and the special case of analysis of variance. The second edition (date of first not mentione
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