Modern Experimental Design
Wiley Series in Probability and Statistics
1. Auflage Februar 2007
624 Seiten, Hardcover
Wiley & Sons Ltd
Kurzbeschreibung
This volume covers the first full year of experimental design topics at the beginning graduate level with a well balanced, down-to-earth, and complete presentation, covering both design and analysis equally. Mathematical rigor is kept to a minimum with up-to-date discussions on hard-to-change factors, the selection of factor levels in terms of physical units, designs with more than one response variable, and multi-response optimization are also included due to the intense applicability to the industrial sector.
A complete and well-balanced introduction to modern experimental design
Using current research and discussion of the topic along with clear applications, Modern Experimental Design highlights the guiding role of statistical principles in experimental design construction. This text can serve as both an applied introduction as well as a concise review of the essential types of experimental designs and their applications.
Topical coverage includes designs containing one or multiple factors, designs with at least one blocking factor, split-unit designs and their variations as well as supersaturated and Plackett-Burman designs. In addition, the text contains extensive treatment of:
* Conditional effects analysis as a proposed general method of analysis
* Multiresponse optimization
* Space-filling designs, including Latin hypercube and uniform designs
* Restricted regions of operability and debarred observations
* Analysis of Means (ANOM) used to analyze data from various types of designs
* The application of available software, including Design-Expert(r), JMP(r), and MINITAB(r)
This text provides thorough coverage of the topic while also introducing the reader to new approaches. Using a large number of references with detailed analyses of datasets, Modern Experimental Design works as a well-rounded learning tool for beginners as well as a valuable resource for practitioners.
1. Introduction.
2. Completely Randomized Design.
3. Designs that Incorporate Extraneous (Blocking) Factors.
Graeco-Latin Square Design.
4. Full Factorial Designs with Two Levels.
5. Fractional factorial Designs with Two-Levels.
6. Designs With More Than Two Levels.
7. Nested Designs.
8. Robust Designs.
9. Split-Unit, Split-Lot, and Related Designs.
10. Response Surface Designs.
11. Repeated Measure Designs.
12. Multiple Responses.
13. Miscellaneous Design Topics.
14. Tying It All Together.
Answers to Selected Exercises.
Appendix: Statistical Tables.
Author Inde.
Subject Index.
