Quantitative Techniques
Subject Overview
Quantitative Techniques equips M.Com students with the statistical and operations-research toolkit used throughout the program — central tendency, dispersion, correlation and regression, probability distributions, linear programming and game theory, and transportation, assignment and project scheduling (PERT/CPM) problems. A 4-credit core theory paper.
Unit-wise Syllabus
4 units — click WhatsApp below to get the full notes for each
Unit 1: Descriptive statistics
Meaning, features, functions, scope and limitations of statistics, measures of central tendency (arithmetic/geometric/harmonic mean, mode, median, quartiles/deciles/percentiles), measures of variation (range, quartile deviation, mean deviation, standard deviation and coefficients), moments, skewness (Karl Pearson and Bowley measures) and kurtosis
Unit 2: Correlation, regression and probability
Simple/multiple/partial and linear/non-linear correlation, scatter diagrams, Pearson's correlation coefficient, rank correlation, simple regression via least squares, relationship between correlation and regression, approaches to probability, addition and multiplication laws, conditional probability and Bayes' theorem
Unit 3: Probability distributions, LP and game theory
Binomial, Poisson and Normal distributions with properties and applications, formulation of linear programming problems, graphic and Simplex (including Big-M) solution methods, degeneracy, duality, post-optimality analysis, two-person zero-sum games, pure and mixed strategies, dominance rule, graphic solution to games
Unit 4: Transportation, assignment and project scheduling
Transportation problem — North-West Corner, Least Cost and Vogel's Approximation methods, optimality testing via MODI method; assignment problem via the Hungarian method; PERT/CPM project networks, scheduling with known activity times, critical path