Quantitative Techniques for Business – Adv – Teach To India

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Quantitative Techniques for Business – Adv

Exam Preparation for Quantitative Techniques for Business: This model paper is designed for graduation students as per the latest ... Show more
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Model Question Paper

Quantitative Techniques for Business

 

Key Features

  • Unit-wise Short Notes 
    Each unit includes a summary in both languages, making revision faster and more effective.
  • Extensive MCQ Practice 
    1500+ MCQ Practice Questions: This comprehensive question bank includes 1500+ multiple-choice questions (MCQs). Each unit contains approximately 150 MCQs covering a wide range of cognitive levels such as remembering, understanding, application, and analysis.

  • Exam Practice Paper with Mock Tests 
    Includes three full-length mock tests for real exam practice. 

  • Latest Syllabus as per NEP 
    The syllabus aligns with the latest National Education Policy (NEP) and follows the exam patterns of MSU, CCSU, and other universities following the NEP.

  • Designed by Experts 
    This question bank has been meticulously prepared by subject matter experts to ensure accuracy and relevance.

Why Choose This Model Paper?

  • Complete Exam Preparation: Unit-wise summaries, MCQ practice, and mock tests provide a complete study solution.
  • Latest NEP-Based Pattern: Ensures compliance with the latest university exam structure.

Program Class: Diploma / B.B.A

Year: I

Semester: II

Subject: B.B.A-201

Course Title: Quantitative Techniques for Business

Credits: 4

Core Compulsory

Max. Marks: –25+75

Min. Passing Marks: 33

Unit

Topics

I

Statistics: Types of Data, Classification & Tabulation of Data, Frequency Distribution, Census and Sample Investigation, Diagrammatical and Graphical Presentation of Data.

 

II

Measures of Central Tendency (Mean, Median & Mode) Measures of Dispersion (Range, Mean Deviation & Standard Deviation).

 

III

Correlation: significance of Correlation, Types of Correlation, Scatter Diagram Method, Karl Pearson coefficient of correlation, Spearman’s coefficient of Rank correlation. Regression: Introduction, Regression Lines and Regression Equations & Regression Coefficients.

 

IV

Analysis of Time Series, Index Numbers, Interpolation and Extrapolation.

V

Probability: Definitions of Probability, Additive and Multiplicative Rules of probability, Bay’s Theorem (Simple numerical) Probability Distributions: Binomial, Poisson and Normal.

 

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