FULLY SOLVED BOOK LASY 5 YEARS PAPERS SOLVED PLUS GUESS
Quantitative Techniques
Quantitative Techniques
Section 1 QUANTITATIVE TECHNIQUES – INTRODUCTION
Unit 1 Historical Development, About Quantitative Technique, Methodology of Quantitative Techniques, Formulating the Problem
Unit 2 Defining the Decision Variables and Constraints, Developing a Suitable Model, Acquiring the Input Data, Solving the Model, Validating the Model, Implementing the Results, Advantages of Mathematical Modeling
Unit 3 Scope of Quantitative Technique, Statistics : An Introduction, Origin and Growth of Statistics, Meaning and Definition of Statistics
Unit 4 Statistics as Data, Statistics as a Science, Statistics as a Science different from Natural Sciences, Statistics as a Scientific Method, Statistics as a Science or an Art, Systems Concepts.
Section 2 MEASURES OF CENTRAL TENDENCY
Unit 5 Definition of Average, Functions and Characteristics of an Average, Various Measures of Average, Arithmetic Mean, Median, Other Partition or Positional Measures, Mode, Relation between Mean, Median and Mode, Geometric Mean, Harmonic Mean.
Section 3 MATHEMATICAL MODEL
Unit 6 Mathematics — The Language of Modelling, Building a Mathematical Model, Verifying and Refining a Model, Variables and Parameters, Continuous-in-Time vs. Discrete-in-Time Models, Deterministic Model Example, Probabilistic Models.
Section 4 LINEAR PROGRAMMING: GRAPHICAL METHOD
Unit 7 Essentials of Linear Programming Model, Properties of Linear Programming Model, Formulation of Linear Programming, General Linear Programming Model
Unit 8 Maximization & Minimization Models, Graphical Method, Solving Linear Programming Graphically Using Computer, Summary of Graphical Method.
Section 5 LINEAR PROGRAMMING: SIMPLEX METHOD
Unit 9 Additional Variables used in Solving LPP, Maximization Case, Solving LP Problems Using Computer with TORA, Minimization LP Problems, Big M Method, Degeneracy in LP Problems, Unbounded Solutions in LPP, Multiple Solutions in Lpp, Duality in LP Problems, Sensitivity Analysis.
Section 6 PROBABILITY
Unit 10 Classical Definition of Probability, Counting Techniques, Statistical or Empirical Definition of Probability, Axiomatic or Modern Approach to Probability, Theorems on Probability-I, Theorems on Probability-II
Section 7 THEORETICAL PROBABILITY DISTRIBUTIONS
Unit 11 Probability Distribution, Binomial Distribution, Hypergeometric Distribution, Pascal Distribution, Geometrical distribution, Uniform Distribution (Discrete Random Variable), Poisson Distribution, Exponential Distribution, Uniform Distribution (Continuous Variable), Normal Distribution
Section 8 PROBABILITY DISTRIBUTION OF A RANDOM VARIABLE
Unit 12 Probability Distribution of a Random Variable, Discrete and Continuous Probability Distributions, Cumulative Probability Function or Distribution Function
Unit 13 Mean and Variance of a Random Variable, Theorems on Expectation, Joint Probability Distribution, Marginal Probability Distribution, Conditional Probability Distribution
Unit 14 Expectation of the Sum or Product of two Random Variables, Expectation of a Function of Random Variables Decision Analysis under Certainty, Decision-making under Uncertainty, Decision-making under Risk
Unit 15 Expected Value with Perfect Information (EVPI), Use of Subjective Probabilities in Decisionmaking, Use of Posterior Probabilities in Decision-making.