Unit 1

Basic Principles for designing statistical experiments: Randomisation, Replication and local control techniques; determination of experimental units and notion of experimental error. Analysis of variance with one–way and two–way classifications; Models and Methods of analysis.

Unit 2

Completely randomized and randomized block designs – Models and estimates of parameters and their standard error – Analysis of data arising from such designs, Analysis when one or two observations are missing.

Unit 3

Latin Square Design – Model – Estimation of parameters – Method of analysis – Missing Plot technique in LSD – Analysis of covariance – One-way classification only

Unit 4

Multiple Comparison tests: LSD , Student-Newman–Keuls test , Duncan’s Multiple range test, Tukey’s test – Transformations to stabilize the variance .

Unit 5

Factorial Experiments: 2 2 , 23 and 32 designs; estimation of main effects and interactions and their standard errors – Principles of confounding

CO1: Compare the pairs of treatment means using different methods when null hypothesis in rejected in ANOVA.
CO2: Analyze the data using split plot, strip plot and general factorial experiments.
CO3: Construct fractional factorial experiments and apply confounding in real life problems.
CO4: Understand the analysis of BIBD, PBIBD, Quasi-Latin square, and cross over design and their applications in agriculture, business and industries

Text Books

1. Das.M.N. and Giri.N.C. (1986): Design and Analysis of Experiments, Wiley eastern. 2. Gupta .S.C. and Kapoor.V.K.(2000): Fundamentals of Applied Statistics, Sultan Chand.

Reference Books

1. Montgomery, D.C. (2001)) Design and Analysis of Experiments, John Wiley.
2. Kempthorne. O. (1965): The Design and Analysis of Experiments , Wiley eastern.
3. Goon.A.M, Gupta and Dasgupta.B. (2001): An Outline of statistical theory, vol. II, 6/e World Press Calcutta.
4. Parimal Mukhopadhyay(2005):Applied Statistics, 2/e, Books and Allied (P) Ltd, Kolkata