Joseph Voelkel Headshot

Joseph Voelkel

Professor
School of Mathematical Sciences
College of Science

585-475-2231
Office Location
Office Mailing Address
2544 Carey, or CQAS, RIT 98 Lomb Memorial Dr Rochester, NY 14626-5604

Joseph Voelkel

Professor
School of Mathematical Sciences
College of Science

Education

BS, Rensselaer Polytechnic Institute; MS, Northwestern University; Ph.D., University of Wisconsin-Madison

Bio

Dr. Voelkel has taught courses in experimental design, regression analysis, reliability statistics, statistical computing, theory of statistics, multivariate analysis, statistical process control, and capstone.

His consulting and training through RIT have included a wide range of clients, including those in the films, optics, electronics, resin, plastics, automotive, laser, pharmaceutical, and bearing industries. The list includes Bausch & Lomb, Borden, DuPont, General Motors, ITT, Mobil, Motorola, Tenneco, and Xerox. His focus ranges from explaining fundamental statistical methods and mentoring Six-Sigma-project teams to teaching advanced statistical techniques and developing novel statistical methods to solve client-specific problems.

585-475-2231

Currently Teaching

STAT-792
3 Credits
This course is designed to provide a capstone experience for MS students at the end of the graduate studies, and will require a synthesis of knowledge obtained from earlier coursework.
STAT-611
3 Credits
This course is an introduction to two statistical-software packages, SAS and R, which are often used in professional practice. Some comparisons with other statistical-software packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; built-in functions; creation of new functions or macros; graphics; matrices and arrays; simulations; select statistical applications.
STAT-731
3 Credits
This course introduces the students to the fundamental principles of modern graduate level statistical theory with a strong emphasis on conceptual aspects of estimation theory and statistical inference along with an exploration of the modern computational techniques needed in the application/implementation of the methods covered. Topics include fundamentals of probability theory for statistics, random variable with a focus on the understanding and use of probability distribution function (both probability density function and cumulative distribution function), quantiles of a distribution, understanding and use of the mathematical expectation operator, special discrete and continuous distributions, and distributions of functions of random variables and their use in statistical modelling, sums of random variables as used in statistics, point estimation, limit theorems, properties of estimators (bias, variance, mean squared error, consistency, efficiency, sufficiency), bias variance trade-off, interval estimation, hypothesis testing, bootstrap approach to estimation and inference, and elements of computational statistics.

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Published Conference Proceedings
Voelkel, Joseph G. "The Missing-Index Problem in Process Control." Proceedings of the Quality and Productivity Research Conference 2013. June 5-7, 2013, Niskayuna, NY. Ed. Martha Gardner, Program Chair. Niskayuna, NY: http://www.qprc2013.com/uploads/SPC_Apps_2-Voelkel-Misiing-Index_Problem_in_Process_Control-QPRC2013.pdf, 2013. Web.