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M4251 Design and analysis of experiments

Syllabus: Geometric interpretation of least squares, ANOVA as a linear model. Principles of blocking, including randomized blocks, Latin squares, Graeco-Latin squares, balanced incomplete block designs. Sample size and power. Random factors. Determination of expected mean squares. Nested factors. Fractional factorial experiments. Confounding. Response surfaces.

Prerequisites: A 2nd or 3rd Year course covering one-way ANOVA, two-way ANOVA, randomised; Block and factorial experiments; Familiarity with MINITAB; Multiple regression (the Regression Analysis component (RA) will provide a more than adequate background for this component)

References:
Cox, D.R., Planning of experiments, Wiley 1958.
Daniel, C., Application of statistics to industrial experimentation, New York, Wiley, 1976.
Hicks, C.R., Fundamental concepts in the design of experiments, Holt, Rinehart and Winston, 1982
Montgomery, D.C., Design and analysis of experiments, Second ed., New York, Wiley 1984.

Lecturer: Aidan Sudbury



 
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