This is an advanced course in Design of Experiments that aims at describing some advanced level topics for students who wish to pursue research in Design of Experiments. This course prepares students for undertaking research in this area.
Course |
Course Outcomes |
Learning and teaching strategies |
Assessment Strategies |
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Course Code |
Course Title |
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24STT423(A) |
Advanced Design of Experiments (Theory) |
CO 130: Analyze the data and apply incomplete block design to the data. CO 131: Construct the design for the provided data using finite fields and MOLS. CO 132: Plan and execute screening experiments to select factors that affect the process. CO 133: Analyze and apply research in Design of Experiments. CO 134: Examine factors at three levels and mixed levels. CO 135: Contribute effectively in course-specific interaction. |
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. |
Desirable properties of a good design: orthogonality, connectedness and balancing. Various optimality criteria and their interpretations. Relation between blocks of incomplete block designs, duality, resolvability and affine resolvability.
Finite Group and finite field, finite geometry projective and Euclidean., Finite geometry and different method of mols, inter and intra block analysis of BIBD. Constructions of orthogonal Latin squares - (i) for prime power numbers and (ii) by Mann-Mechneish theorem.
Group divisible design. Lattice Design, Linked Block Design, Two-associate PBIBD, association scheme and intra block analysis.
Fractional Factorial Design, Orthogonal and balanced arrays and their connections with confounded and fractional confounded.
Orthogonality, rotatibility and blocking, construction and analysis, method of steepest ascent.
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