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B. Stat. – 203 |
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| Aim of the Course | ||||||||||||||||||
| The main aim of this course is to analyze the differences among group means and their associated procedures (such as “variation” among and between groups), developed by Ronald Fisher. Comparisons of mean squares, along with an F-test allow testing of a nested sequence of models. | ||||||||||||||||||
| Objective of the Course | ||||||||||||||||||
| After completing this Course, student should | ||||||||||||||||||
| ⇒ | Learn how to analyze the total variation to its component variation; | |||||||||||||||||
| ⇒ | Notice the pairwise difference whether it is significant or not. | |||||||||||||||||
| ⇒ | Understand comparative design are Important to choose between alternatives with narrow scope, suitable for initial comparison | |||||||||||||||||
| Learning Outcomes | ||||||||||||||||||
| At the end of the course, the students will be able to | ||||||||||||||||||
| ⇒ | know when it is appropriate to use ANOVA; | |||||||||||||||||
| ⇒ | know when it is appropriate to use ANCOVA; | |||||||||||||||||
| ⇒ | know where and how an appropriate design should be applied. | |||||||||||||||||
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| Course Contents | ||||||||||||||||||
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Analysis of Variance: Definition, Assumptions, Analysis of variance (ANOVA) corresponding to one-way, two-way and three-way classifications, fixed, random and mixed effect models, Parametric function and contrasts, Variance components analysis.
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Analysis of Covariance: Introduction, Concomitant variable, Analysis of covariance in one-way, two-way and three-way classifications with one concomitant variable.
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Experimental Design: Basic concept, Principles of experimental design, Requirements of a good experiment.
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Orthogonal Design: Completely randomized design, Randomized block design, Analysis including interaction effects, Latin square design, Efficiency of a design, Missing plot technique in RBD and LSD.
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Factorial Experiment: Basic ideas, description and analysis of 2p, 3p, p×q factorial experiments, Confounding, Split plot design.
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| Main Books Recommended: | ||||||||||||||||||
| 1) | Montgomery D. C. (2011). Design and Analysis of Experiments, 9th ed. [Solution] | |||||||||||||||||
| 2) | Cohran and Cox (2000): Experimental Design, 2nd ed., John Wiley, N.Y. | |||||||||||||||||
| 3) | Federer, W.T. 1955. Experimental design, Mcmillan, New York. [Ryan] | |||||||||||||||||
| 4) | Fisher, R.A.(1995): Design of Experiment, 8th ed., Hafner, N.Y. [Hinkleman] | |||||||||||||||||
| References: | ||||||||||||||||||
| 5) |
Brown, S. R., & L. E. Melamed (1990). Experimental design and analysis. [Dean]
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| 6) |
Gerber, A. S., & D. P. Green (2012). Field experiments: Design, analysis, and interpretation. New York: WW Norton. [Petersen]
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| 7) |
Kleijnen, J. P. (2008). Design of experiments: overview. In Simulation Conference, 2008. WSC 2008. Winter. IEEE.
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| 8) |
Wang, W. Z., S. S., Mao & L. R. Zeng (2004). Design and analysis of experiments. lecture notes. [Miller]
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