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MMPC 005 Quantitative Analysis for Managerial Applications | Quick Readable Notes For IGNOU Exam

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MMPC 005 Quantitative Analysis for Managerial Applications | Quick Readable Notes For IGNOU Exam

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A comprehensive guide to mastering quantitative analysis techniques for managerial decision-making in financial management. This book is essential for MBAFM students to excel in exams and practical applications.
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  • Comprehensive coverage of quantitative techniques.
  • Step-by-step problem-solving methods.
  • Real-world business applications.
  • Quick review notes for exam preparation.
Category : MASTER‘S DEGREE PROGRAMMES
Sub Category : Master of Business Administration –Financial Management (MBAFM)
Products Code : MBAFM-MMPC-S1-5.06
HSN Code : 490110
Language : English
Author : BMAP EDUSERVICES PVT LTD
Publisher : BMAP EDUSERVICES PVT LTD
University : IGNOU (Indira Gandhi National Open University)
Pages : 100-130
Weight : 157gms
Dimensions : 21.0 x 29.7 cm (A4 Size Pages)



Details

"MMPC 005 Quantitative Analysis for Managerial Applications" is a meticulously designed textbook for MBAFM students, focusing on the quantitative techniques crucial for financial management. This book covers a wide range of topics, from basic statistical methods to advanced quantitative analysis tools, ensuring that students gain a robust understanding of the subject.

Benefits of Using This Book:

  • Exam Preparation: Provides quick, readable notes that cover the entire syllabus within 100-130 pages, making it easier to revise efficiently.
  • Practical Applications: Enhances the ability to apply quantitative methods to real-world business scenarios.
  • Comprehensive Understanding: Breaks down complex concepts into simple, step-by-step explanations.
  • Boosts Confidence: Equips students with the skills needed to tackle quantitative problems confidently in exams and managerial roles.

Content Overview:

  • Basic Statistical Techniques: Mean, median, mode, standard deviation.
  • Probability Theory: Basic concepts, probability distributions, and their applications.
  • Regression Analysis: Simple and multiple regression, interpretation of results.
  • Forecasting Methods: Time series analysis, moving averages, exponential smoothing.
  • Linear Programming: Formulation, graphical and simplex methods, sensitivity analysis.
  • Decision Analysis: Decision trees, utility theory, risk analysis.

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