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  1. Direction of Research in Statistics and Applied Statistics:Physical Sciences and Engineering John Borkowski Professor of Statistics Montana State University www.math.montana.edu/~jobo

  2. Outline • A review of research areas appearing in journals related to the physical sciences and engineering • chemistry, chemical engineering, manufacturing, industrial engineering, … • A brief discussion of possible ways to develop an active research program

  3. Review of Selected Publications • I reviewed titles of articles published in three popular journals related to statistical theory and applications in the physical sciences and engineering: • Journal of Quality Technology(JQT) • Technometrics (Techno) • Quality Engineering (QE)

  4. Review of Selected Publications Time Period:2003 to 2008 5+ years Number of Articles: 635 • JQT155 articles • Technometrics193 articles • QE287 articles

  5. Review of Selected Publications Categorized into 5 areas of research: • Statistical Quality Control / Statistical Process Control (SQC/SPC) • Design of Experiments / Response Surface Methodology (DOE/RSM) • Reliability (REL) • Modeling (MOD) • Other (OTHER)

  6. Review of Selected Publications • Each of the 5 areas had multiple research categories. • Many articles were classified into 2 or 3 research categories. • 842 research category classifications across the 635 articles.

  7. Summary by Research Area JQT Techno QETotal SQC/SPC 90 88 187 365(43.5%) DOE/RSM 130 68 60 258 (30.6%) Modeling 22 55 19 96 (11.4%) Reliability 13 29 18 60( 7.1%) Other 7 19 37 63( 7.4%) ----------------------------------------------------------------- Total 262 259 321 842

  8. The Future of SQC/SPC ? • Product/Process Profile Analysis • Multivariate Control Charts (Sampling plans? Response vector contains both continuous and discrete response variables?) • New applications of SQC/SPC (To genomics / proteomics data? To microarray data? To ecological processes and spatial processes?)

  9. The Future of RSM/DOE ? • “Space-filling” designs for irregularly-shaped regions(applications of orthogonal arrays, Latin hypercubes, uniform designs ?) • Mixture designs with many components in highly-constrained regions(applications of orthogonal arrays, Latin hypercubes, uniform designs ?) • Restrictions on randomization, split-plotting(in mixture experiments, with categorical responses?) • Desirability functions + optimal design(How do we combine several design evaluation criteria?) • Genetic algorithms(Can we apply GAs to the problems above?)

  10. The Future of Modeling? • Generalized linear models + response surface methodology (Response optimization? Robust designs?) • Model and variable selection Information criteria (e.g. AIC)? Model averaging? Bayesian methods? • Classification and Regression Trees ?

  11. Some Thoughts on Developing an Active Research Program • Networking • Working with other statisticians • Working with other researchers who are not statisticians

  12. Networking • Attend conferences • Present research at conferences • Introduce yourself to other researchers • Do not be afraid to ask questions • Personal example: Dr. Greg Piepel, a statistician at Pacific Northwest National Laboratories (PNNL), USA • Result: I became Visiting Faculty at PNNL, submitted research for publication in JQT

  13. Networking • Keep in contact with other researchers (For example: former students) • Personal example: In 2005, I was invited by Thammasat University to be a Visiting Faculty member because of a former PhD student from my university who now teaches in Thailand. • Result: I have been a Visiting Faculty member for 4 summers, and I am involved in TU student research, received a Fulbright scholarship, attended conferences and visited other universities in Thailand, Thailand Statistician

  14. Working with other statisticians • Read abstracts of journal articles as often as possible so that you are aware of current research topics • Be patient. • Personal Example: Nam-Ky Nguyen (Hanoi, Vietnam) asked me to be co-author on research paper • Result: Publication in JSPI (2008) and invitation to work on World Bank Problem in Vietnam

  15. Working with other researchers who are not statisticians • Many researchers need statistical help (consulting, data analysis, summarizing results) • Personal Example: I work with researchers in ecology and environmental science, biology, earth science, … • Result: I have received money from their research grants and published in their journals: J. of Wildlife Management, J. of Range Management, Weed Science,…

  16. Some Observations • I believe there is potential for collaborative research • within Thailand • between Thailand and other countries • The problem is to determine what opportunities exist and then how to address them • The solution begins with communication (primarily networking)

  17. How well do you know your colleagues ? • Do you know what your colleagues are interested in ? • Do you know what their specialty areas are in statistics ? • Do you know which colleagues are interested in collaborative research ?

  18. Things to Consider • Create a directory of statisticians who want to develop their research program • Determine if they have any specific research areas of interest • Determine if they have any specific research problems that require collaboration (Conduct a survey ?)

  19. Things to Consider • Many U.S. universities have funded international programs that allow faculty to visit other countries for research • Contact directors of these programs expressing interest in developing a relationship with your organization (e.g., exchange of faculty and students) • Many international faculty would like to visit Thailand

  20. This presentation will be available soon atwww.math.montana.edu/~jobo