Presentation on theme: "1 The Effective Industrial Statistician: Necessary Knowledge and Skills William Q. Meeker Department of Statistics Center for Nondestructive Evaluation."— Presentation transcript:
1 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
2 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
3 Evolution of the Industrial Statistician Snapshot at 1975 Snapshot today Can we extrapolate into the future?
4 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 ChemicalAmoco Bell Labs DuPont GEGM IBMKodak Pratt and WhitneyProctor and Gamble RCAShell How many remain?
5 The Industrial Statisticians 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
6 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
7 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
8 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.
9 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
10 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: –Todays Industrial Statistician works almost exclusively in collaborations with scientists, engineers, managers, and other non-statisticians. –Interpersonal skills are extremely important Unknown
11 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
12 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 clients area.
13 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
14 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
15 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 companys business and the science and engineering used there, broad in perspective, and proactive in their work.