This course will enable the students to assess the knowledge of all the statistical aspects for business decisions in the quantitative manner and preparing the research report using appropriate statistical techniques.
Course |
Learning outcomes (at course level) |
Learning and teaching strategies |
Assessment Strategies |
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Course Code |
Course Title |
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24CBTM501 |
Quantitative Techniques for Business Decisions (Theory)
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CO181: Formulate, solve, and interpret linear programming problems, contributing to analytical capabilities and problem-solving skills in various domains. CO182: Formulate, solve, and interpret transportation and assignment problems, contributing to decision-making skills in logistics, operations management, and related fields. CO183: Analyse, model, and optimize networks in various domains, contributing to problem-solving skills in network-related fields. CO184: Analyse complex decision-making situations and make rational choices under uncertainty, integrating concepts of probability, utility, and risk to optimize outcomes. CO185: Examine strategic interactions among decision-makers in various contexts using game theory, identifying equilibrium outcomes, and understanding the implications for decision-making and cooperation. CO186: Contribute effectively in course-specific interaction |
Approach in teaching: Interactive sessions, Discussion, Tutorials, Reading assignments, Demonstration
Learning activities for the students: Self learning assignments, Effective questions, Presentation, Solving questions-based problems, Project tasks
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Continuous Assessment Test, Semester end examinations, Quiz, Assignments, Presentation, Individual and group projects |
Operations Research and Linear Programming
Operations Research: An Introduction, Characteristics, Nature, Scope and Role of Operations Research and Quantitative Techniques, Scientific approach in decision-making, Techniques of OR, Limitations of these Techniques.
Linear Programming: Formulation of L.P. Problems, Graphical Solution and Simplex Method, Big-M method and Two-phase method; Duality
Transportation and Assignment Technique
Elementary Transportation: Formulation of Transport Problem, Solution by N.W. Corner Rule, Least Cost method, Vogel’s Approximation Method (VAM), Modified Distribution Method. (Special cases: Multiple Solutions, Maximization case, Unbalanced case, prohibited routes)
Elementary Assignment: Hungarian Method, (Special cases: Multiple Solutions, Maximization case, Unbalanced case, Restrictions on assignment.)
Network Analysis
Network Analysis: Construction of the Network diagram, Critical Path- float and slack analysis (Total float, free float, independent float), PERT, Project Time, Crashing
Decision Theory
Decision Theory: Pay off Table, Opportunity Loss Table, Expected Monetary Value, Expected opportunity Loss, Expected Value of Perfect Information and Expected profit for Perfect Information, Decision Tree
Introduction to Game Theory
Introduction to Game Theory: Pay off Matrix- Two person Zero-Sum game, Pure strategy, Saddle point; Dominance Rule, Mixed strategy, Reduction of m x n game and solution of 2x2, 2 x s, and r x 2 cases by Graphical and Algebraic methods
Suggested Readings:
E-Resources: