Buch, Englisch, 488 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 728 g
Buch, Englisch, 488 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 728 g
Reihe: Chapman & Hall/CRC Texts in Statistical Science
ISBN: 978-0-367-45047-2
Verlag: Chapman and Hall/CRC
Many scientists and technologists would like to carry out their own statistical analyses without reference to a professional statistician. Often, however, they have no knowledge of statistics or otherwise do not know how to apply it to research and development problems. The first edition of Statistics in Research and Development was written for these people. The second edition brings the book up-to-date.
The text is divided into two parts; the first introduces basic but very important statistical techniques whilst the second part presents the modern powerful methods of data analysis that are particularly useful in modern research and development. Problems are provided at the end of each chapter with worked solutions provided at the end of the book. A problem-centered approach is used throughout and care has been taken to choose problems with which the scientist or technologist can identify. The results of the statistical analyses are reinterpreted into the language of the scientist. Mathematics is kept to a minimum and the assumptions underlying each technique are clearly explained. All the techniques introduced are powerful and proven, and commercial computer programs are available for many of them.
Zielgruppe
Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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
