Analysis of Variance and Design of Experiments

Paper Code: 
STT 602
Credits: 
3
Contact Hours: 
45.00
Max. Marks: 
100.00
Objective: 

This paper aims at teaching the students about Analysis of Variance and Design of Experiment.

Course

Learning outcomes (at course level

Learning and teaching strategies

Assessment Strategies

 

Paper Code

Paper Title

STT-602

Analysis of Variance and Design of Experiments

 

CO 63: Able to identify the behaviour of the experimental unit.

 

CO 64: Able to construct the design and deal the problems of real world situation.

 

CO 65: Ability to take decision on the output of the design and also identify the outliers.

 

Approach in teaching:

Interactive Lectures,

Group Discussion,

Classroom Assignment

Problem Solving Sessions

 

Learning activities for the students:

Assignments

Seminar

Presentation

Subject based  Activities

Classroom Quiz

Assignments

Class Test

Individual Presentation

 

8.00
Unit I: 
Analysis of Variance - I:

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.

 

9.00
Unit II: 
Analysis of Variance – II:

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.

 

9.00
Unit III: 
Design of Experiments – I:

Need for design of experiments, Meaning of experiment, experimental unit, treatment, field, block, experimental error, precision, uniformity trials, choice of size and shape of plots and blocks. Fundamental principles of design of experiments- replication, randomization and local control, Efficiency of design

 

10.00
Unit IV: 
Design of Experiments – II:

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 and two missing values in RBD

 

9.00
Unit V: 
Design of Experiments – III:

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- 22 and 23 experiments, main effects, interaction effects and their analysis.

Essential Readings: 
  • Goon, A.M. Gupta, M.K. and Dasgupta, B. (2001): Fundamentals of Statistics (Volume II), The World Press Pvt Ltd, Kolkata, VII Edition,
  • Gupta, S.C. &. Kapoor, V.K. (2000): Fundamentals of Applied Statistics,Sultan Chand & Sons, New Delhi tenth edition.
  • Das, M.N. and Giri, N.C. (2002): Design and Analysis of Experiments, New Age  International Publisher, Second Edition.
  • Joshi, D.D. (2003): Linear Estimation and Design of Experiments, New Age   International Publisher.
  • Montgomery D.C.(1952): Design and Analysis of Experiments, Sixth Edition, Wiley  Eastern Ltd. Limited
  • Cochran, W.G. and Cox, G.M.(1997): Experimental Design, Asia Publishing House, third edition.

 

 

Academic Year: 
2021-2022
  • Printer-friendly version
  • PDF version