MBA 103 Course Plan

  • Programme Code 039
  • Course Code MBA-103
  • Course TypeCore
  • Programme Master of Business Administration
  • Course Name Quantiative Techniques
  • L - T/P - Credits 3 - 0 - 3
  • Course Outcome
  • CO1 Identify and differentiate between different statistical techniques and methods
  • CO2 Explain the merits and limitations of various statistical techniques.
  • CO3 Demonstrate effective computational and spreadsheets skills for business analysis.
  • CO4 CO4: Analyse and interpret statistical information from the business data and reports.
  • CO5 Apply quantitative techniques to solve a variety of business problems.
Unit No. Lecture No. Topic Sessional Outcome Mapping with CO ICT Tools / Class Material (PPT ) First Shift Second Shift Guest Lecture Expert Lecture
1 L1 Statistics Introduction The student will be able to understand Statistics. CO1, CO2
1 L2 Measures of central tendency - Mean The student will be able to understand Mean CO1
1 L3 Measures of central tendency - Median The student will be able to understand and apply Median CO1
1 L4 Measures of central tendency - Mode The student will be able to understand and apply Mode CO1
1 L5 Measure of Dispersion- Mean Deviation The student will be able to understand Measure of Mean Deviation CO1
1 L6 Measure of Dispersion- Standard Deviation The student will be able to understand Measure of Standard Deviation CO1
1 L7 Measure of Dispersion - Skewness The student will be able to understand Measure of Skewness CO1
1 L8 Measure of Dispersion - Kurtosis The student will be able to understand Measure of Kurtosis CO1
1 L9 Concept of dispersion , measures of dispersion Able to understand concept of dispersion CO1
1 L10 Skewness and Kurtosis Able to understand skewness and kurtosis CO1
1 L11 Bivariate analysis Students will analyze problems of bivariate analysis CO1
1 L12 Correlation and measures of correlation Student will be able to Understand correlation Analysis CO1, CO2, CO3
1 L13 Regression Student will be able to Understand regression Analysis CO1
1 L14 OLS regression coefficients Student will be able to Understand OLS
1 L15 Regression and correlation Analysis Students will b profiency in solving regression and correlation numerical on spreadsheet CO1, CO2, CO3
1 L16 Decision making based on regression analysis Students will apply regression analysis in decision Making CO1, CO2, CO3
2 L17 Probability Analysis Introduction Students will be able to understand conceept of probability CO1, CO2, CO3
2 L18 Basic numericals of probability Students profiency in solving numerical of probability CO1
2 L19 Theorems of probability Students will understand concept of probability CO1
2 L20 Numericals based on addition and multiplication theorems Students able to solve numericals of probability CO1
2 L21 Bayes theorem Students will understand Bayes theorem and practical use of it. CO1
2 L22 Probability distribution Continuous and Discrete Students will learn aboutProbability distribution Continuous and Discrete CO1
2 L23 Binomial Distribution, Poisson Distribution, Normal Distribution Students will differentiate between Binomial Distribution, Poisson Distribution, Normal Distribution CO1
2 L24 Application of probability in decision making Students will Application of probability in decision making CO1
3 L25 Linear Programming Model: Meaning , Assumptions, Formulation of Linear Programming Model Students will learn about LP Model CO1, CO2
3 L26 LPP Solution : Graphical Method Students will analyze LP Problem through Simplex Method CO1, CO2, CO3
3 L27 LPP Simplex Method Students will analyze Problem through Graphical Model CO1, CO2, CO3
3 L28 Assignment Model Students will learn about Assignment Model, a problem solving method CO1
3 L29 Assignment Hungarian Model for Solving LPP Students will learn to solve problem through hungarian model. CO1, CO2, CO3
3 L30 Travelling Sales man Modelling Theory Understand and remember the meaning and types of listening CO2, CO3, CO4, CO5
3 L31 Travelling Sales man Modelling Problem Students will learn how to solveAssignment Problem through Travelling Sales man Modelling CO1, CO2, CO3
3 L32 Transportation Model infeasible solution Students will learn about Transportation Model CO1, CO2, CO3
3 L33 Testing of Optimality Students will solve problem for Testing of Optimality CO1, CO2, CO3
3 L34 Concept of Transhipment Students will get concept about Transhipment. CO1
4 L35 Decision Theory Students will learn about Decision Theory CO1
4 L36 States of Decision Making Students willunderstandStates of Decision Making. CO1
4 L37 Decision Tree Analysis Students will analyze Decision Tree CO1
4 L38 Game Theory concept Students will learn about. CO1
4 L39 Types of Game Students will understand Types of Game CO1
4 L40 Principles of Dominance Students will apply Principle of Dominance. CO1
4 L41 Solution of Game Algebraic Method Students will evaluate problem through Algebraic Method CO1, CO2, CO3
4 L42 Solution of Game Graphical Atudent will apply Graphical Method to get Solution of Game CO1, CO2, CO3
4 L43 Solution of Game Simplex Method Atudent will apply simplex Method to get Solution of Game CO1, CO2, CO3
4 L44 Revision & Doubt Clear Session Students will remember Topics learnt in
4 L45 Discussion of Previous Question Papers Students will discuss on Previous Year Question Paper

# As per Scheme & Syllabus Of Guru Gobind Singh Indraprastha University, New Delhi 2022-23 Onwards.