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EB

EB

ONLINE

Pardubice : University of Pardubice, 2017

1 online zdroj (142 stran) : ilustrace

ISBN 978-80-7560-069-1 (online ; pdf) ISBN !978-80-7560-069-0 (chyb.)

ISBN 978-80-7560-068-4 (print)

This book brings a review of basic methods for design and evaluation of experiments. It shows the principal steps and explains the causes of dispersion and errors of the measured values, as well as statistical methods for their evaluation. It is shown how the measured values can be described by simple characteristics or probability distributions. Then, characterisation of relations between investigated quantities is described, including fitting of the data by regression functions. It is explained how confidence intervals can be created, which contain the true values of the parameters, and how many tests are necessary for obtaining the results with the demanded accuracy or for the verification of a certain hypothesis. One chapter is devoted to the theory of similarity and dimensional analysis, which help one to reduce the extent of experiments and make the results more general. Other chapters explain the analysis of variance, design of experiments, and experimental finding of a maximum or minimum. These procedures facilitate finding of the most important factors and optimum parameters. Sensitivity analysis shows how variations of the input quantities cause deviations of the investigated quantity from the optimum or nominal value. The last chapter is devoted to the efficient tools for the study of random influences, such as the Monte Carlo simulation technique. The use of the described methods is illustrated on examples and the individual chapters are supplemented by references..

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CONTENTS // 1. Introduction 7 // 2. Principal steps of experimental research 9 // 3. Errors and variance of measured values 15 // 4. Basics of probability and statistics // for experimental analysis 19 // 5. Determination of characteristics // of investigated quantities 33 // 6. Relationships of two and more quantities 43 // 7. Fitting of empirical data by regression functions 51 // 8. Confidence intervals, testing of hypotheses, // and the necessary amount of data 65 // 9. Dimensional analysis and theory of similarity 81 // 10. Analysis of variance (ANOVA) 97 // 11. Design of experiments (DOE) 103 // 12. Experimental finding of maximum or minimum 113 // 13. Sensitivity analysis 121 // 14. Simulation methods for study of random quantities // and influences 127 // Index 137