This paper aims at teaching the students about Analysis of Variance and Design of Experiment.
Linear Model and its different types (only introduction). Concept of ANOVA (i).One-way classified data.(ii)Two-way classification with one observation per cell. Fixed effect models of (i) and (ii) and the assumptions involved. Effects of violation of assumptions made in ANOVA.
Estimation of treatment effects and treatment differences. Expectation of sum of squares, variance of the estimates for both one-way and two-way classified data and critical difference.
Need for design of experiments, Meaning of experiment, experimental unit, treatment, field, block, experimental error, precision, uniformity trials. Fundamental principles of design of experiments- replication, randomization and local control, Efficiency of design choice of size and shape of plots and blocks.
Basic designs( with one observation per cell and fixed effects model)- Completely Randomized Design, Randomized Block Design - Analysis of these designs, standard error of treatment differences, efficiency of RBD over CRD, their advantages , disadvantages and usages. Missing Plot Techniques, Estimation of single missing value in RBD
Latin Square Design – Its analysis, least square estimates, expectation of sum of squares, efficiency of LSD over CRD and RBD. Estimators of single missing value in LSD. Factorial experiments- 2 2 experiments, main effects, interaction effects and their analysis.
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