Statistics as a Catalyst to Learning by Scientific Method Part II—A Discussion

References

• Box, G. E. P. (1954). “Contribution to the Discussion on the Symposium on Interval Estimation”. Journal of the Royal Statistical Society B 16, pp. 211–212.
   Google Scholar
• Box, G. E. P. (1980a). “Sampling and Baye's Inference in Scientific Modelling and Robustness” (with discussion). Journal of the Royal Statistical Society A 143, pp. 383–430.
   Google Scholar
• Box, G. E. P. (1980b). “Sampling Inference, Baye's Inference and Robustness in the Advancement of Learning” in Bayesian Statistics edited by J. M. Bernardo, M. H. DeGroot, D. V. Lindley, and A. F. M. Smith. University Press, Valencia, Spain.
   Google Scholar
• Box, G. E. P. (1983). “An Apology for Ecumenism in Statistics” in Scientific Inference, Data Analysis, and Robustness edited by G. E. P. Box, T. Leonard, and C-F. Wu. Academic Press, London, UK.
   Google Scholar
• Box, G. E. P. (1997). “Scientific Method: The Generation of Knowledge and Quality”. Quality Progress 30, pp. 47–50.
   Google Scholar
• Box, G. E. P. and Behnken, D. W. (1960). “Some New Three Level Designs for the Study of Quantitative Variables”. Technometrics 2, pp. 455–475.
   Google Scholar
• Box, G. E. P. and Bisgaard, S. (1993). “What Can You Find Out From 12 Experimental Runs?” Quality Engineering 5, pp. 663–668.
   Google Scholar
• Box, G. E. P., Bisgaard, S. and Fung, C. (1987). “Designing Industrial Experiments: The Engineer's Key to Quality”. Course Notes, Center for Quality and Productivity Improvement, University of Wisconsin, Madison, WI.
   Google Scholar
• Box, G. E. P. and Cox, D. R. (1964). “An Analysis of Transformations”. Journal of the Royal Statistical Society B 26, pp. 211–243.
   Google Scholar
• Box, G. E. P. and Drapper, N. R. (1987). Empirical Model-Building and Response Surfaces. John Wiley & Sons, New York, NY.
   Google Scholar
• Box, G. E. P. and Fung, C. A. (1986). “Minimizing Transmitted Variation By Parameter Design”. Technical Report No. 8, Center for Quality and Productivity Improvement, University of Wisconsin, Madison, WI.
   Google Scholar
• Box, G. E. P. and Fung, C. A. (1993). “Is Your Robust Design Procedure Robust?” Quality Engineering 6, pp. 503–514.
   Google Scholar
• Box, G. E. P. and Hau, I. (1998). “Response Surface Methods With Multiple Linear Constraints” submitted to the Technical Report Series, Center for Quality and Productivity Improvement, University of Wisconsin, Madison, WI.
   Google Scholar
• Box, G. E. P. and Hunter, J. S. (1954). “A Confidence Region for the Solutions of a Set of Simultaneous Equations with an Application to Experimental Design”. Biometrika 41, pp. 190–199.
   Web of Science ®Google Scholar
• Box, G. E. P. and Hunter, J. S. (1961). “The 2k–p Fractional Factorial Design, I”. Technometrics 3, pp. 449–458.
   Web of Science ®Google Scholar
• Box, G. E. P. and Jones, S. (1992a). “Designing Products That Are Robust to the Environment”. Total Quality Management 3, pp. 265–282.
   Google Scholar
• Box, G. E. P. and Jones, S. (1992b). “Split-plot Designs for Robust Product Experimentation”. Journal of Applied Statistics 19, pp. 3–26.
   Google Scholar
• Box, G. E. P. and Luceño, A. (1997). Statistical Quality Control by Monitoring and Feedback Adjustment. John Wiley & Sons, New York, NY.
   Google Scholar
• Box, G. E. P. and Meyer, R. D. (1993). “Finding the Active Factors in Fractionated Screening Experiments”. Journal of Quality Technology 25, pp. 94–105.
   Web of Science ®Google Scholar
• Box, G. E. P. and Tidwell, P. D. (1962). “Transformation of the Independent Variables”. Technometrics 4, pp. 531–550.
   Web of Science ®Google Scholar
• Box, G. E. P. and Tyssedal, J. (1994). “Projective Properties of Certain Orthogonal Arrays”. Technical Report No. 116, Center for Quality and Productivity Improvement, University of Wisconsin, Madison, WI.
   Google Scholar
• Box, G. E. P. and Tyssedal, J. (1996). “Projective Properties of Certain Orthogonal Arrays”. Biometrika 83, pp. 950–955.
   Web of Science ®Google Scholar
• Box, G. E. P. and Wetz J. (1973). “Criteria for Judging Adequacy of Estimation by an Approximating Response Function”. Technical Report No. 9, Department of Statistics, University of Wisconsin, Madison, WI.
   Google Scholar
• Box, G. E. P. and Wilson, K. B. (1951). “On the Experimental Attainment of Optimum Conditions” (with discussion). Journal of the Royal Statistical Society B 13, pp. 1–45.
   Google Scholar
• Box, G. E. P. and Youle, P.V. (1955). “The Exploration and Exploitation of Response Surfaces: An Example of the Link Between the Fitted Surface and the Basic Mechanism of the System”. Biometrics 11, pp. 287–323.
   Web of Science ®Google Scholar
• Daniel, C. (1961). “Sequences of Fractional Replicates in the 2p–9 Series”. Journal of the American Statistical Association 57, pp. 403–429.
   Web of Science ®Google Scholar
• Deming, W. E. (1950). Some Theory of Sampling. John Wiley & Sons, New York, NY. Reprinted in 1984 by Dover Publications, New York, NY.
   Google Scholar
• Deming, W. E. (1982). Out of the Crisis. Center for Advanced Engineering Studies, Massachusetts Institute of Technology, Cambridge, MA.
   Google Scholar
• Duncan, J. A. (1974). Quality Control and Industrial Statistics, 4th ed. Richard D. Irwing, Homewood, IL.
   Google Scholar
• Finney, D. J. (1945). “The Fractional Replication of Factorial Arrangements”. Annals of Eugenetics 12, pp. 291–301.
   Google Scholar
• Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd, Edinburgh, UK.
   Google Scholar
• Hellstrand, C. (1989). “The Necessity of Modern Quality Improvement and Some Experiences With Its Implementation in the Manufacture of Rolling Bearings”. Philosophical Transactions of the Royal Society A 327, pp 529–537.
   Google Scholar
• Kim, K-J. and Lin, D. K. J. (1998). “Dual Response Surface Optimization: A Fuzzy Modeling Approach”. Journal of Quality Technology 30, pp. 1–11.
   Web of Science ®Google Scholar
• Lin, K. J. and Draper, N. R. (1992). “Projection Properties of Plackett and Burman Designs”. Technometrics 4, pp. 423–428.
   Google Scholar
• Lin, K. J. (1993a). “A New Class of Supersaturated Designs”. Technometrics 35, pp. 28–31.
   Web of Science ®Google Scholar
• Lin, K. J. (1993b). “Another Look at First-order Saturated Designs: The p-Efficient Designs”. Technometrics 35, pp. 284–292.
   Web of Science ®Google Scholar
• Lin, K. J. (1995). “Generating Systematic Supersaturated Designs”. Technometrics 37, pp. 213–225.
   Web of Science ®Google Scholar
• Lucas, J. M. (1996). “The 1996 W. J. Youden Address: System Change and Improvement: Guidelines for Action When the System Resists”. American Statistical Association Proceedings.
   Google Scholar
• Meyer, R. D.; Steinberg, D. M.; and Box, G. E. P. (1996). “Follow–up Designs to Resolve Confounding in Fractional Factorials”. Technometrics 38, pp. 330–313.
   Google Scholar
• Michaels, S. E. (1964). “The Usefulness of Experimental Designs” (with discussion). Applied Statistics 13, pp. 221–235.
   Web of Science ®Google Scholar
• Morrison, S. J. (1957). “The Study of Variability in Engineering Design”. Applied Statistics 6, pp. 133–138.
   Web of Science ®Google Scholar
• Plackett, R. L. and Burman J. P. (1946). “The Design of Optimum Multifactorial Experiments”. Biometrika 33, pp. 305–325 and pp. 328–332.
   Web of Science ®Google Scholar
• Shewhart, W. (1939). Statistical Method: From the Viewpoint of Quality Control. Lancaster Press, Lancaster, PA.
   Google Scholar
• Taguchi, G. (1986). Introduction to Quality Engineering: Designing Quality into Products and Processes. Kraus International Publications, White Plains, NY.
   Google Scholar
• Vining, G. G. and Myers, R. H. (1990). “Combining Taguchi and Response Surface Philosophies: A Dual Response Approach”. Journal of Quality Technology 22, pp. 38–45.
   Web of Science ®Google Scholar
• Yates, F. (1937). “The Design and Analysis of Factorial Experiments”. Technical Communication No. 35, Imperial Bureau of Soil Science, Harpenden, England.
   Google Scholar