Statistics in Research and Development

This book covers experimental design and the more advanced techniques of data analysis which can be used to assess performance, to compare methods and to control quality. It is useful to anyone concerned with the development or the management of complex processes in any industry.

List of contents

1. What is statistics? 2. Describing the sample 3. Describing the population 4. Testing and estimation: One sample 5. Testing and estimation: Two samples 6. Testing and estimation: Qualitative data 7. Testing and estimation: Assumptions 8. Statistical process control 9. Detecting process changes 10. Investigating the process-an experiment 11. Why was the experiment not successful? 12. Some simple but effective experiments 13. Adapting the simple experiments 14. Improving a bad experiment 15. Analysis of variance 16. An introduction to Taguchi techniques

About the author

R. Caulcutt

Summary

This book covers experimental design and the more advanced techniques of data analysis which can be used to assess performance, to compare methods and to control quality. It is useful to anyone concerned with the development or the management of complex processes in any industry.

Product details

• Authors: R. Caulcutt, R. (University of Bradford Caulcutt
• Assisted by: Chris Chatfield (Editor of the series), Jim Lindsey (Editor of the series), Jim Zidek (Editor of the series)
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 31.12.2019
• EAN: 9780367450472
• ISBN: 978-0-367-45047-2
• No. of pages: 488
• Series: Chapman & Hall/CRC Texts in Statistical Science
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Social sciences, law, business > Business > Miscellaneous; MATHEMATICS / Probability & Statistics / General, TECHNOLOGY & ENGINEERING / Quality Control, TECHNOLOGY & ENGINEERING / Industrial Engineering, SCIENCE / Applied Sciences, TECHNOLOGY & ENGINEERING / Research, Probability & statistics, Probability and statistics, Industrial quality control