Author	Gertsbakh, Ilya. author
Title	Measurement Theory for Engineers [electronic resource] / by Ilya Gertsbakh
Imprint	Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2003
Connect to	http://dx.doi.org/10.1007/978-3-662-08583-7
Descript	XIII, 150 p. online resource

The emphasis of this textbook is on industrial applications of Statistical Measurement Theory. It deals with the principal issues of measurement theory, is concise and intelligibly written, and to a wide extent self-contained. Difficult theoretical issues are separated from the mainstream presentation. Each topic starts with an informal introduction followed by an example, the rigorous problem formulation, solution method, and a detailed numerical solution. Each chapter concludes with a set of exercises of increasing difficulty, mostly with solutions. The book is meant as a text for graduate students and a reference for researchers and industrial experts specializing in measurement and measurement data analysis for quality control, quality engineering and industrial process improvement using statistical methods. Knowledge of calculus and fundamental probability and statistics is required for the understanding of its contents

1 Introduction -- 2 Mean and Standard Deviation -- 3 Comparing Means and Variances -- 4 Sources of Uncertainty: Process and Measurement Variability -- 5 Measurement Uncertainty: Error Propagation Formula -- 6 Calibration of Measurement Instruments -- 7 Collaborative Studies -- 8 Measurements in Special Circumstances -- Answers and Solutions to Exercises -- Appendix A: Normal Distribution -- Appendix B: Quantiles of the Chi-Square Distribution -- Appendix C: Critical Values of the Fโdistribution -- References

1. Mathematics
2. Probabilities
3. Physical measurements
4. Measurement
5. Statistics
6. Applied mathematics
7. Engineering mathematics
8. Industrial engineering
9. Production engineering
10. Quality control
11. Reliability
12. Industrial safety
13. Mathematics
14. Probability Theory and Stochastic Processes
15. Measurement Science and Instrumentation
16. Appl.Mathematics/Computational Methods of Engineering
17. Quality Control
18. Reliability
19. Safety and Risk
20. Statistics for Engineering
21. Physics
22. Computer Science
23. Chemistry and Earth Sciences
24. Industrial and Production Engineering