3 Hours/Week, 3 Credits

Linear estimation, estimable parametric functions and conditions for estimability, methods of estimation for analysis of variance models, solution of normal equations for less than full rank, optimality properties of least squares estimators, test of hypothesis. Weighing design: method of estimation. Use of incomplete blocks, construction and analysis of BIB designs, incomplete block design as weighting designs (intra and inter-block analysis). Missing plot. Orthogonal Latin squares. Youden squares. Lattice designs. Partially balanced incomplete block designs. Factorial experiment: sn factorial experiments and their analysis. Confounding, total, partial and simultaneous confounding in two and three levels up to n factors, fractional replicates and their construction. Asymmetric factorial experiments. Split-plot design: analysis of split-plot design, split-split-plot design: analysis of split-split-plot design, strip-plot design: analysis of strip-plot design, nested design: analysis of nested design. Analysis of covariance: analysis of covariance of non-orthogonal data in two-way classification. Analysis of covariance with one and more than one ancillary variables. Covariance and analysis of experiments with missing observations, transformation.