MPEM 5120
Application and Design
of Industrial Experiments

Instructor
Charles “Chip” Todd, Associate Professor of Mathematical Science, Montana Tech

Text
Statistics for Experimenters, Second Edition; G.E.P. Box, W.G. Hunter, and J.S. Hunter. Wiley & Sons, 1978

General Policies and Procedures

• Homework assignments, individual and group projects (if applicable), etc., are designed to help the student understand and apply the course material to engineering problem solving situations in a professional manner. Therefore, grades will be determined on the basis of timeliness, adherence to requirements, content accuracy, originality, and overall appearance.
• Except for extra ordinary circumstances, no make-up exams will be given and no late assignments will be accepted.
• Due to administrative and research responsibilities of the instructor beyond this course, it may occasionally be necessary to reschedule an office hour. All efforts will be made to prevent disruption of class time. If absolutely necessary to miss class time, however, additional outside work or an alternate method of a make-up will be required (College of Engineering policy prevents arbitrary cancellation of a scheduled course meeting).

Grading Policies

Description
Key topics that are to be discussed (tentative, not necessarily order of coverage)

• Statistics in the scientific process
• Basis of inference and decision making
• Developing hypothesis tests and interpretation of error
• Correlation studies
• Sampling strategies
• Statistical independence
• Comparison of one and two treatment effects
• Comparison of more than two treatment effects (ANOVA)
• Designed experimentation (randomized blocks, factorial, replicated, split-plot, repeated measures, cross-over designs, others)
• Empirical model building
• Simple regression analysis with assumptions and validation
• Multiple regression analysis with assumptions and validation
• Time series and forecasting techniques
• Other multivariate techniques (factor analysis, cluster analysis, etc)

Objectives
To provide an overview of applied statistical experimental design and analysis techniques for a broad range of engineering disciplines. The overview will include both fundamental and advanced concepts in experimental design and scientific methodology. An emphasis will be placed upon two broad areas:  the design of statistical experiments; and the interpretation of statistical results to support decision making and design functions in engineering.

Questions or Comments:
Kumar Ganesan ● MPEM Director ● 406-496-4239
Cindy Dunstan ● Graduate School ● 406-496-4304