Illustrating the Practice of Statistics as a Stepping Stone to Statistical Engineering

ABSTRACT As students prepare for statistical engineering, they first need to learn about the practice of statistics. This article presents some of the realities of the practice of statistics. These realities include looking at the bigger picture, dealing with data quality issues, developing an appropriate statistical model using the context and knowledge of the client, and designing follow-on studies. The practice of statistics is illustrated with precipitation data collected by a meteorologist.

[1]  W. J. Studden,et al.  Optimal Experimental Designs , 1966 .

[2]  Michael J. Mazu,et al.  Design and Analysis of Gauge R&R Studies , 2006, Technometrics.

[3]  P. Smaglik.  Closing the gap , 2005, Nature.

[4]  Michael de la Maza,et al.  Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992) , 1993 .

[5]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[6]  Alyson G. Wilson,et al.  Finding Near-Optimal Bayesian Experimental Designs via Genetic Algorithms , 2001 .

[7]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[8]  John K Kruschke,et al.  Bayesian data analysis. , 2010, Wiley interdisciplinary reviews. Cognitive science.

[9]  D. Montgomery,et al.  Design and analysis of gauge R&R studies : making decisions with confidence intervals in random and mixed ANOVA models , 2005 .

[10]  L. Gleser.  Measurement, Regression, and Calibration , 1996 .

[11]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[12]  R. Carroll.  Measurement, Regression, and Calibration , 1994 .

[13]  Mike Carnell,et al.  Rediscovering True North: Customer satisfaction must remain a priority , 2010 .

[14]  M. Degroot.  Optimal Statistical Decisions , 1970 .

[15]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .