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QUANTITATIVE TECHNIQUES
1. DECISION MAKING AND QUANTITATIVE TECHNIQUES
 Problem solving and decision making
 Quantitative analysis and decision making
 Steps in quantitative analysis
 Methods of cost, revenue, and profit
 Quantitative methods in practice
2. INTRODUCTION TO LINEAR PROGRAMMING
 Business problems and their solution through linear programming: Overview of
LP; construction of a LP problem and model.
 Solution to a linear programming problem: Graphical method ( including peculiar
situations); Simplex method (for both unrestricted variable and negative variables,
included) in case of (a) maximization with less than/ equal to situation, (b)
minimization with greater than/ equal to case, (c) maximization with mixed type,
and (d) minimization with mixed type.
 Duality problem: Economic interpretation of duality; derivation of a dual solution
and vice-versa for a linear programming problem( of all kinds)
3. MANAGERIAL APPLICATIONS OF LINEAR PROGRAMMING
 Marketing problems and their solutions through linear programming
 HR problems and their solutions through L.P.
 Production and inventory issues and their resolution
 Financial allocations and L.P. solutions
4. DIFFERENTIAL CALCULUS
 Differential calculus: Rules of differentiation through formula (Algebraic,
exponential, and logarithmic)
5. APPLICATIONS OF DIFFERENTIAL CALCULUS TO BUSINESS
PROBLEMS
 Applications in the field of demand analysis, elasticity of demand, supply
analysis, market equilibrium (calculation of price and equilibrium quantity); cost
analysis, and revenue analysis (including cases of cost minimization and profit
maximization)
6. PARTIAL DIFFERENTIATION
 Partial differentiation: Rules of partial differentiation
7. APPLICATIONS OF PARTIAL DIFFERENTIATION
 Estimating marginal utility
 Cross elasticies
 Marginal product estimates.
8. MATRICES AND DETERMINANTS-1
 Definition
 Types of matrices
 Matrix operations – addition, subtraction, multiplication and division.
9. MATRICES AND DETERMINANTS-2
 Calculation of value of determinant
 Adjoint of a matrix
 Row operations
 Inverse operations
 Applications of matrices to business problems
 Input-output analysis
10. MARKOV ANALYSIS
Principle and its application in business problems, namely:
 Prediction of market shares for future periods and at equilibrium.
 Evaluation of marketing strategies for improvement in market shares &
evaluation of repair & maintenance policies.
 Prediction of bad loans.
11. PROBABILITY
 Basic probability concepts and probability rules – marginal/simple probability,
conditional and joint probability.
 Revising prior probability – Bayers’ theorem of posterior probability.
 The concept of probability distributions.
 Application of probability concepts in business/management.
12. PROBABILITY DISTRIBUTIONS
 Random variables
 Discrete random variables
 Binomial probability distribution
 Poisson probability distribution
 Continuous random variables
 Normal probability distribution
13. APPLICATION OF PROBABILITY CONCEPTS IN BUSINESS
 Decision making and probability analysis
14. PROJECT SCHEDULING:PERT/CPM
 Construction of Network diagram
 Types of Floats: Total, Free &Interfering floats
 Crashing for determination of optimum duration of project.
15. REVIEW OF QUANTITATIVE TECHNIQUES
 Mock test
Reference books


Andersen, Sweeney, and Williams: An Introduction to Management Science
(South-Western: 2005): Chs.1-6
N.D.Vohra: Quantitative Techniques in Management (THM: Latest edition):
Relevant chapters