Unit I : Principles of Experimentation
Basic concepts – terminology in experimental designs – experiment – treatment – experimental unit – blocks – experimental error – principles – randomization, replication and local control – error control – selection of experimental material – uniformity trials – determination of optimum plot size – maximum curvature method.
Unit II : ANOVA and Mean comparisons
Analysis of variance – assumptions in analysis of variance – effects of failure of assumptions – identification and remedies – Data transformation – logarithmic, angular and square root transformations – multiple comparisons – critical difference (least significant difference) and Duncan's multiple range test (DMRT).
Unit III : Single factor experiments
Designs for laboratory and field experiments – single factor experiments – Completely Randomised Design (CRD) with equal and unequal replications – layout of CRD – analysis of CRD – advantages and disadvantages of CRD – Randomised Block Design (RBD) – layout of RBD – analysis of RBD – advantages and disadvantages of RBD – efficiency of RBD over CRD – missing plot technique in RBD (one and two missing observations) – analysis of covariance (RBD) – multi-observation data.
Unit IV : Factorial experiments
Concept of factorial experiments – factor – levels of a factor – simple, main and interaction effects – advantages and disadvantages of factorial experiments – symmetrical and asymmetrical factorial experiments – comparison of single factor experiments and factorial experiments – 2n factorial experiments – analysis using regular method (RBD) – Yates algorithm – asymmetrical factorial experiment (up to 3 factors).
Unit V : Designs for Factorial experiments
Split-plot design – lay out – analysis – advantages and disadvantages – strip plot design – layout – analysis – advantages and disadvantages – split-split-plot design – layout – analysis.