5 UBMSFSI 5. Business Statistics

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[50 lectures: 3 Credit]

 

 

  • Business mathematic is important as managers need to know “How much” profit they would earn, whether it is cumulative or no.

 

  • It also helps the managers to understand the co-relation of different variables of his business.
Unit   Title No. of
      Lectures
     
Unit I INTRODUCTION TO STATISTICS 12
  Functions/Scope  
  Importance  
  Limitations  
    DATA:  
 
  • Relevance of Data(Current Scenario)
 
 
  • Type of data(Primary & Secondary)
 
 
  • Primary(Census vs Samples, Method of Collection (In Brief)
 
 
  • Secondary(Merits, Limitations, Sources) (In Brief)
 

 

 

PRESENTATION OF DATA:

 

  • Classification – Frequency Distribution – Discrete & Continuous

 

  • Tabulation
  • Graph(Frequency, Bar Diagram, Pie Chart, Histogram, Ogives)

 

 

MEASURES OF CENTRAL TENDENCY:

 

  • Mean(A.M, Weighted, Combined)
  • Median(Calculation and graphical using Ogives)

 

  • Mode(Calculation and Graphical using Histogram)
  • Comparative analysis of all measures of Central Tendency

 

 

 

 

Unit II   MEASURES OF DISPERSION: 12
 
  • Range with C.R(Co-Efficient Of Range)
 
  Quartiles & Quartite deviation with CQ (Co-Efficient Of
    Quartile)  
  Mean Deviation from mean with CMD (Co-Efficient Of Mean

 

Deviation)

 

  • Standard deviation with CV(Co-Efficient Of Variance)
  • Skewness & Kurtosis (Only concept)

 

 

CO-RELATION:

 

  • Karl Pearson
  • Rank Co-Relation

 

 

LINEAR REGRESSION:

 

  • Least Square Method

 

 

Unit IIITIME SERIES: 12

 

  • Least Square Method
  • Moving Average Method
  • Determination of Season

 

 

INDEX NUMBER:

 

  • Simple(unweighted) Aggregate Method
    • Weighted Aggregate Method

 

  • Simple Average of Price Relatives
  • Weighted Average of Price Relatives
  • Chain Base Index Numbers
  • Base Shifting, Splicing and Deflating
  • Cost of Living Index Number

 

 

Unit IV PROBABILITY: 14

 

  • Concept of Sample space
  • Concept of Event
  • Definition of Probability
  • Addition & Multiplication laws of Probability
  • Conditional Probability

 

  • Bayes’ Theorem(Concept only)
  • Expectation & Variance
  • Concept of Probability Distribution(Only Concept)

 

 

DECISION THEORY:

 

  • Acts
  • State of Nature Events

 

  • Pay offs
  • Opportunity loss
  • Decision Making under Certainty
  • Decision Making under Uncertainty

 

  • Non-Probability: Maximax, Maximin, Minimax, Regret, Laplace &Hurwicz)

 

  • Probabilitistics(Decision Making under risk)

–          EMV

 

–          EOL

 

–          EVPI

 

  • Decision Tree

 

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