Course Name- Experimental Design

Course No: STAT 0511 

Credit hours = 3 (2-1-0)

Course Objectives

This course is meant for students of agricultural and animal sciences other than Statistics. Designing an experiment is an integrated component of research in almost all sciences. The students would be exposed to concepts of Design of Experiments so as to enable them to understand the concepts involved in planning, designing their experiments and analysis of experimental data.

Course outcome (CO-PSO Mapping)

PSO1 : Impart knowledge and understanding of fundamental concepts and techniques of maintaining and enhancing soil fertility, crop production, crop management, crop improvement, biodiversity and sustainability of agriculture worldwide.
PSO3 : Apply knowledge of basic science through Agricultural microbiology, Plant biochemistry and Biotechnology.

Syllabus 

Theory:

UNIT I: Need for designing of experiments, characteristics of a good design. Basic principles of designs- randomization, replication and local control.

UNIT II: Uniformity trials, size and shape of plots and blocks; Analysis of variance; Completely randomized design, randomized block design and Latin square design.

UNIT III: Factorial experiments, (symmetrical as well as asymmetrical) orthogonality and partitioning of degrees of freedom, Confounding in symmetrical factorial experiments, Factorial experiments with control treatment.

UNIT IV: Split plot and strip plot designs; Analysis of covariance and missing plot techniques in randomized block and Latin square designs; Transformations, crossover designs, balanced incomplete block design, resolvable designs and their applications ~ Lattice design, alpha design - concepts, randomisation procedure, analysis and interpretation of results. Response surfaces. Experiments with mixtures.

UNIT V: Bioassays- direct and indirect, indirect assays based on quantal dose response, parallel line and slope ratio assays potency estimation

Practical:

Uniformity trial data analysis, formation of plots and blocks, Fairfield Smith Law; Analysis of data obtained from CRD, RBD, LSD; Analysis of factorial experiments without and with confounding; Analysis with missing data; Split plot and strip plot designs; Transformation of data; Analysis of resolvable designs; Fitting of response surfaces.

Session Plans (Theory):

Theory Lecture (1) :

Need for designing of experiments, characteristics of a good design.

Basic principles of designs- randomization, replication and local control.

Theory Lecture (2-4): 

Uniformity Trials, Size and Shape of Plots and Blocks.

oneway and two classified data

Theory Lecture (5-8):

Fundamentals Of Design Experimental Designs

Completely randomized design

Randomized block design and

Latin square design

Theory Lecture (9-11):

Factorial experiments, (symmetrical as well as asymmetrical) orthogonality and

partitioning of degrees of freedom,

Theory Lecture (12-13):

Confounding in symmetrical factorial experiments, Factorial experiments with control treatment.

Pdf notes

Theory Lecture (14-16):

Split Plot and Strip Plot Designs

Theory Lecture (17-19):

Analysis of Covariance (ANCOVA) and

Missing Plot Techniques in Randomized Block and Latin Square Designs.

Theory Lecture (20-23):

Data Transformations

Crossover designs

Balanced incomplete block design (BIBD)

Resolvable designs and their applications

Theory Lecture (24-27):

Lattice design

Alpha design

Response surfaces

Experiments with mixtures

Theory Lecture (28-32):

Bioassays- direct and indirect,

Indirect assays based on quantal dose response,

Parallel line and slope ratio assays potency estimation.

Revisions

Session Plan (Practical):

Practical Lecture (1-2):

Uniformity trial data analysis, formation of plots and blocks, Fairfield Smith Law

Practical Lecture (3-5):

Analysis of data obtained from CRD, RBD, LSD

Practical Lecture (6-8):

Analysis of factorial experiments without and with confounding

Practical Lecture (9-10):

Analysis with missing data (RBD & LSD)

Practical Lecture (11-13):

Split plot and strip plot designs; Transformation of data

Practical Lecture (14-16):

Analysis of resolvable designs; Fitting of response surfaces

Revisions

E-material

Experimental Design

Assignment and Question bank

Assignment of Experimental Design

Question Bank