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Quantitative Analysis for Management Applications
Detailed Syllabus Plan
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Block I: Basic Mathematics For Management
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1. Quantitative Decision Making: An Overview
Introduction to Quantitative Decision-Making Process, Managerial
Decision-Making System & Environment, Managerial Decision Models
and Algorithms, Quantitative Models and Algorithms
2. Functions and Progressions
Functions, Types of Functions, Equations, Applications of
Functions in Business Situations, Fitting a Linear Curve, Fitting
a quadratic cost curve. Progressions, Arithmetic progressions,
Geometric Progressions, Annuities, loans and mortgages, Perpetual
annuities and infinite series
3. Matrix Algebra Applications
Matrices, Use of matrices for production planning, Solution of
linear equations using matrices, The best method of solving linear
equations, Transpose of a matrix, Brand switching and Markov
chains. Determinants, Solution of linear equations using
determinants, Higher Order Determinants, Main properties of
determinants, Managerial problems involving determinants
4. Spread Sheet Applications
Quantitative methods applications in business using
spread-sheets
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Block II: Data Collection and Analysis
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5. Collection of Data
Data Collection and Presentation, Requirements of Data in the
Organisation, Basic Classification of Data, Primary Data,
Secondary Data, Sampling
6. Presentation of Data
Data Presentation, Cumulative Frequency Curve or Ogive Curve
7. Measure of Central Tendency
Data Analysis, Mean, Mode, Median, Understanding and Using
Averages, 3Ms of Statistics: Comparison
8. Measures of Variation and Skewness
Measuring Dispersion, Skewness
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Block 3: Probability And
Probability
Distributions
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9. Basic Concepts of Probability
Probability Concepts, Permutations, Combinations, The Binomial
Theorem, Probability Distributions
10. Discrete Probability Distributions
Introduction to discrete probability Distributions,
Interpretation of discrete probability Distributions
11. Continuous Probability Distributions
Introduction to and interpretation of continuous probability
Distributions
12. Decision Theory
Introduction to Decision Theory, Minimax Analysis
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Block 4: Sampling And
Sampling
Distributions
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13. Sampling Methods
Sampling, Theory of Sampling, Methods of Sampling, Sampling
Reliability, Sampling and Non-Sampling Errors
14. Sampling Distributions
Frequency Distributions used in Sampling
15. Testing of Hypotheses
Inferential Decision Making, The Conceptual Model for
Inferential Decisions, The Quantitative Models of Inferential
Decisions, Algorithms and Applications, The General Inferential
Decision Algorithm, Specific Decision Areas, The Mean Problem, The
More Than Two-Sample Mean Problem
16. Chi Square Tests
Chi-square test and its applications
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Block 5: Forecasting Methods
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17. Business Forecasting
Forecasting, The Conceptual Model, The Mathematical Model,
Algorithms and Applications
18. Correlation
Correlation and its applications, The Parametric Case, The
Non-Parametric Case
19. Regression
The Regression Algorithm, Simple Linear Regression Analysis, The
Exponential Fit, The Modified Exponential Fit, Multiple Regression
Analysis, The Smoothing Algorithm
20. Time Series Analysis
Introduction to Time Series Analysis, Linear and Non-Linear
Analysis, Parabola Fit, Exponential Fit
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