Buch, Englisch, 478 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 667 g
Statistical Techniques, Design of Experiments and Stochastic Modeling
Buch, Englisch, 478 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 667 g
ISBN: 978-0-367-53276-5
Verlag: CRC Press
Focusing on the importance of the application of statistical techniques, this book covers the design of experiments and stochastic modeling in textile engineering. Textile Engineering: Statistical Techniques, Design of Experiments and Stochastic Modeling focuses on the analysis and interpretation of textile data for improving the quality of textile processes and products using various statistical techniques.
FEATURES
- Explores probability, random variables, probability distribution, estimation, significance test, ANOVA, acceptance sampling, control chart, regression and correlation, design of experiments and stochastic modeling pertaining to textiles
- Presents step-by-step mathematical derivations
- Includes MATLAB® codes for solving various numerical problems
- Consists of case studies, practical examples and homework problems in each chapter
This book is aimed at graduate students, researchers and professionals in textile engineering, textile clothing, textile management and industrial engineering. This book is equally useful for learners and practitioners in other scientific and technological domains.
Zielgruppe
Academic, Postgraduate, and Professional
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
- Mathematik | Informatik Mathematik Operations Research
- Mathematik | Informatik Mathematik Stochastik
- Technische Wissenschaften Technik Allgemein Industrial Engineering
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Technologie der Textilverarbeitung und Faserverarbeitung
Weitere Infos & Material
1. Introduction 2. Representation and Summarization of Data 3. Probability 4. Discrete Probability Distribution 5. Continuous Probability Distributions 6. Sampling Distribution and Estimation 7. Test of Significance 8. Analysis of Variance 9. Regression and Correlation 10. Design of Experiments 11. Statistical Quality Control 12. Stochastic Modelling
