Academics / Courses / Descriptions / KeepIEMS 463: Statistical Analysis of Designed Experiments
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Prerequisites
Background in linear models at the level of Stat 350, IEMS 304 or IEMS 462-1.Description
The course covers methods of design and construction of experiments and analysis of data obtained from them. Both theory and applications are covered in detail.
Learning Objectives
- Understand the basic principles of experimentation: randomization, blocking, replication, power.
- Apply the basic principles to design experiments to meet specified goals.
- Learn the theory underlying the methods of construction of design and analysis of experiments.
- Analyze data from experiments using graphical plots, analysis of variance (ANOVA) and multiple testing methods.
- Design and perform a multifactor experiment and report results in the form of a project report.
Topics
- Basic concepts of experimentation: randomization, replication, blocking
- Single factor experiments
- Block designs and Latin squares
- Two-factor experiments
- Two-level factorial experiments
- Two-level fractional factorial experiments
- Random and mixed effects models, variance components
- Nested, crossed-nested and split-plot designs
Materials
- Text: Tamhane A. C. (2009), “Statistical Analysis of Designed Experiments: Theory and Applications,'' Publisher: John Wiley.
- Software: Minitab.