A bubble mixture experiment project for use in an advanced design of experiments class

Journal of Statistics Education

Volumn 15, Issue 1, 2007, Pages

  Steiner, Stefan H ^a   Hamda, Michael ^b   Giddings White, Bethany J ^a   Kutsyy, Vadim ^c   Mosesova, Sofia ^a   Salloum, Geoffrey ^d  

^a UNIVERSITY OF WATERLOO   (Canada)

^b LOS ALAMOS NATIONAL LABORATORY   (United States)

^c Guardian Analytics   (United States)

^d CAMOSUN COLLEGE   (Canada)

Author keywords

Constrained experimental region; Generalized linear model; Optimal design; Poisson regression; Robust parameter design

Indexed keywords

EID: 34047168707     PISSN: None     EISSN: 10691898     Source Type: Journal    
DOI: 10.1080/10691898.2007.11889458     Document Type: Article

References (18)

1. Anderson, M.J. (1997), "Bigger and Better Bubbles via Mixture Design," Stat Teaser, September, 1 and 3.
2. Boys, C.V. (1959), Soap Bubbles Their Colors and Forces Which Mold Them, New York: Dover Publications, Inc.
3. Cornell, J. (2002), Experiments With Mixtures, 3rd edition, New York: John Wiley and Sons.
4. Goldfarb, H.B., Borror, C.M., Montgomery, D.C. and Anderson-Cook, C.M. (2005), "Using Genetic Algorithms to Generate Mixture-Process Experiments Designs Involving Control and Noise Variables," Journal of Quality Technology, 37, 60-74.
5. Gelman, A., Carlin, J.B., Stern, H.S. and Rubin, D.B. (2004), Bayesian Data Analysis, 2nd edition, Boca Raton: Chapman and Hall/CRC.
6. 5 Examples of Experiments Conducted by Students," American Statistician, 31, 12-17.
7. Isenberg, C. (1992), The Science of Soap Films and Soap Bubbles, New York: Dover Publications, Inc.
8. Ishikawa, K. (1982), Guide to Quality Control, 2nd revised edition, Tokyo: Asian Productivity Organization.
9. Johnson M.E., Moore L.M., and Ylvisaker D. (1990), "Minimax and Maximin Distance Designs," Journal of Statistical Planning and Inference, 26, 131-148.
10. McCullagh, P. and Nelder, J. (1989), Generalized Linear Models, 2nd edition, London: Chapman and Hall.
11. Montgomery, D. C. (2001), Design and Analysis of Experiments, 5th edition, New York: John Wiley and Sons, Inc.
12. Oldford R.W. and MacKay R.J. (2001), Stat 231 Course Notes, Fall 2001, University of Waterloo, Waterloo, Ontario.
13. Piepel, M.G. and Piepel, G.F. (2000), "How Soil Composition Affects Density and Water Capacity - A Science Fair Project Using Mixture Experiment Methods," STATS, 28, 14-20.
14. Development Core Team (2004), R: a Language and Environment for Statistical Computing, Vienna: R Foundation for Statistical Computing. www.R-project.org
15. Sahrmann, H.F., Piepel, G.F. and Cornell, J.A. (1987), "In Search of the Optimum Harvey Wallbanger Recipe via Mixture Experiment Techniques," American Statistician, 41, 190-194.
16. Spiegelhalter, D., Thomas, A., Best, N. and Lunn, D. (2004), WinBUGS Version 1.4.1 User Manual. www.mrc-bsu.cam.ac.uk/bugs/
17. Steiner, S.H. and Hamada, M. (1997), "Making Mixtures Robust to Noise and Mixing Measurement Errors," Journal of Quality Technology, 29, 441-450.
18. Taguchi, G. (1987), System of Experimental Design, White Plains: Unipub/ Kraus International Publications.