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The Effective Industrial Statistician: Necessary Knowledge and Skills. William Q. Meeker Department of Statistics Center for Nondestructive Evaluation Iowa State University wqmeeker@IAstate.edu. QPRC 2009 IBM, Yorktown Heights, NY 3 June 2009. Overview.

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the effective industrial statistician necessary knowledge and skills

The Effective Industrial Statistician: Necessary Knowledge and Skills

William Q. Meeker

Department of Statistics

Center for Nondestructive Evaluation

Iowa State University

wqmeeker@IAstate.edu

QPRC 2009

IBM, Yorktown Heights, NY

3 June 2009

overview
Overview
  • Evolution of the Industrial Statistician
  • What Applications do Industrial Statisticians See?
  • What Tools Does an Industrial Statistician Need?
  • Statistics Graduate Program
  • Personality of a Statistician
  • Other Skills
  • Internships for Statistics Graduate Students
  • Concluding Remarks
evolution of the industrial statistician
Evolution of the Industrial Statistician
  • Snapshot at 1975
  • Snapshot today

Can we extrapolate into the future?

typical tasks for an industrial statisticians in 1975
Typical Tasks for an Industrial Statisticians in 1975
  • Design experiments
  • Modeling and analysis of data (including general number crunching)
  • Interpret results
  • Training
  • Conduct research for nonstandard problems

Many US statisticians worked in a statistics group within the company, e.g.:

Allied Chemical Amoco

Bell Labs DuPont

GE GM

IBM Kodak

Pratt and Whitney Proctor and Gamble

RCA Shell

How many remain?

the industrial statistician s environment in 2007
The Industrial Statistician’s Environment in 2007
  • Modern statistical software can do an effective job of modeling and analysis of data and designing simple experiments, and readily accessible to all
  • Statisticians tend to get involved in more complicated interdisciplinary problems
  • Training customers (perhaps increased due to six-sigma)
  • Customers do not want pay for research (or even technical reports)
  • Fewer “Statistics Groups.” Most statisticians integrated into product development or manufacturing groups.
  • More need to be proactive, rather than reactive
what applications do industrial statisticians see
What Applications do Industrial Statisticians See?
  • Product quality and manufacturing
    • Product design (including reliability)
    • Process design (including reliability)
    • Process monitoring
    • Warranty and other reliability field data
  • Marketing
  • Financial services
  • Environmental issues
  • Many other business processes
some statistical tools needed by industrial statisticians
Some Statistical Tools Needed by Industrial Statisticians
  • Bayesian Statistics
  • Categorical data methods
  • Censored data analysis
  • Design of experiments
  • Graphical methods
  • Image analysis
  • Multivariate analysis
  • Optimization
  • Regression analysis (linear and nonlinear)
  • Reliability theory
  • Response surface methods
  • Simulation
  • Spatial statistics
  • Statistical computing and programming
  • Survey sampling
  • Time series analysis
what should be in a statistics graduate program core
What Should Be in a Statistics Graduate Program Core?
  • At least two semesters of mathematical statistics (probability and statistics, perhaps stochastic processes).
  • At least two semesters of statistical modeling and methods with applications (linear and nonlinear regression and maximum likelihood)
  • SAS and R (or S-PLUS) use and programming, plus exposure to Excel, JMP or MINITAB
  • A creative project, thesis, and/or a course in consulting, and corresponding internship experience.
which statistical electives
Which Statistical Electives?
  • Design of experiments
  • Statistical methods for reliability
  • Statistical methods for quality
  • Others according to interests
  • Important: While pursuing a graduate degree, you cannot learn everything that you will need.
    • The purpose of education is to learn how to learn.
    • Statisticians should be prepared to learn (and in some cases develop) new methods to meet the needs of the client (through continuing education and self-study).
    • In some cases statisticians may need to suggest hiring an outside consultant for special problems
personality of a statistician
Personality of a Statistician
  • The joke:A statistician is someone who loves to work with numbers but who did not have the personality to be an accountant.
  • The reality:
    • Today’s Industrial Statistician works almost exclusively in collaborations with scientists, engineers, managers, and other non-statisticians.
    • Interpersonal skills are extremely important

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other skills of an effective industrial statistician
Other Skills of an Effective Industrial Statistician
  • Communications skills
    • Written
    • Listening
    • Presentation
    • Interpersonal
  • Leadership skills (needed to be proactive)
  • Knowledge of relevant subject matter areas, e.g.:
    • Biology
    • Business and Finance
    • Chemistry
    • Engineering
    • Genetics
    • Physics
  • Flexibility and adaptability
communications with clients
Communications with Clients
  • Statisticians should strive to learn some of the scientific/engineering background in the area of their client.
  • It is imperative that the statistician learn and use the language, notation, and traditions of the client’s area.
thanks to
Thanks to
  • Mentors at GE
  • Mentors at ISU
  • Colleagues and supervisors at Bell Labs
  • My students
  • My understanding family
  • Interesting/Helpful clients and access to real problems
internships for statistics graduate students
Internships for Statistics Graduate Students
  • Valuable experiences possible (not the same as working in a university consulting lab)
  • Projects may lead to professional society presentations or publications
  • Effectiveness is highly dependent on the kind of project and attention of the mentor
  • Exposure to the business environment will provide perspective in subsequent years of study and for the eventual job search
concluding remarks
Concluding Remarks
  • “Industrial Statistics” is nearly as broad as the Statistics discipline itself.
  • In spite of the new ability for others to do their own data analysis, there will continue to be healthy demand for statisticians in industry (but in somewhat different roles).
  • The truly effective industrial statistician will be knowledgeable about the company’s business and the science and engineering used there, broad in perspective, and proactive in their work.