Advanced Design for Single Factor Experiments
This is an advanced course in Design of Experiments for single factor experiments for students who wish to pursue research in Design of Experiments. This course prepares students for undertaking research in this area. This also helps prepare students for applications of this important subject to agricultural statistics.
- General properties and analysis of block designs. Balancing criteria. M-associate PBIB designs and their association schemes including lattice designs - properties and construction. Properties and construction of mutually orthogonal latin squares.
- Designs for two – way elimination of heterogeneity including lattice square designs, Designs for test treatment – control(s) comparisons, Nested designs, Mating designs. Cyclic designs, Block designs with nested rows and columns.
- Optimality criteria and optimality of designs, Robustness of designs against missing observation, Presence of outlying observation(s), Presence of systematic trend, model inadequacy etc. Diagnostics in design of experiments.
Analysis of Block Designs, Analysis of PBIB designs, Analysis of Lattice designs, Analysis of designs for two way elimination of heterogeneity designs, Analysis of Augmented designs, Analysis of designs for test treatment –Control(s) Comparison, Analysis of Mating designs, Diagnostic Study, Analysis of Lattice square designs.