Transcript Direction of Research in Statistics and Applied Statistics

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
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
Review of Selected Publications
•
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

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)
Review of Selected Publications
Time Period: 2003 to 2008
Number of Articles:
 JQT
155 articles
 Technometrics 193 articles
 QE
287 articles
5+ years
635
Review of Selected Publications
Categorized into 5 areas of research:
1. Statistical Quality Control / Statistical Process
Control
(SQC/SPC)
2. Design of Experiments / Response Surface
Methodology
(DOE/RSM)
3. Reliability
(REL)
4. Modeling
(MOD)
5. Other
(OTHER)
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.
Summary by Research Area
SQC/SPC
DOE/RSM
Modeling
Reliability
Other
JQT
90
130
22
13
7
Techno
88
68
55
29
19
QE Total
187 365 (43.5%)
60
258 (30.6%)
19
96 (11.4%)
18
60 ( 7.1%)
37
63 ( 7.4%)
----------------------------------------------------------------Total
262
259
321
842
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?)
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?)
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 ?
Some Thoughts on Developing an Active
Research Program
• Networking
• Working with other statisticians
• Working with other researchers who are
not statisticians
Networking
•
•
•
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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
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
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 coauthor on research paper
• Result: Publication in JSPI (2008) and
invitation to work on World Bank Problem
in Vietnam
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,…
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)
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 ?
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 ?)
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
This presentation will be
available soon at
www.math.montana.edu/~jobo