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IEMS 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

  1. Understand the basic principles of experimentation: randomization, blocking, replication, power.
  2. Apply the basic principles to design experiments to meet specified goals.
  3. Learn the theory underlying the methods of construction of design and analysis of experiments.
  4. Analyze data from experiments using graphical plots, analysis of variance (ANOVA) and multiple testing methods.
  5. Design and perform a multifactor experiment and report results in the form of a project report.

Topics

  1. Basic concepts of experimentation: randomization, replication, blocking
  2. Single factor experiments
  3. Block designs and Latin squares
  4. Two-factor experiments
  5. Two-level factorial experiments
  6. Two-level fractional factorial experiments
  7. Random and mixed effects models, variance components
  8. Nested, crossed-nested and split-plot designs

Materials

  1. Text: Tamhane A. C. (2009), “Statistical Analysis of Designed Experiments: Theory and Applications,'' Publisher: John Wiley.
  2. Software: Minitab.