B.Com. (CBCS)
Semester- II
CC203: BUSINESS MATHEMATICS AND STATISTICS (6 Credit)
Marks: 100 (Internal Assessment 20+ Term-end 80)
Lectures: 60 Tutorials: 5
Objective: The objective of this course is to familiarize students
with the applications of mathematics and statistical techniques in business
decision-making.
Notes:
a) Use of simple
calculator is allowed.
b) Proofs of
theorems / formulae are not required.
c) Trigonometric
functions are not to be covered.
Part
– A: Business Mathematics (23L+3T) Marks: 10
Unit
I: Matrices
Definition of
a matrix. Types of matrices; Algebra of matrices. Calculation of values of
determinants up to third order; Adjoint of a matrix; Finding inverse of a
matrix through ad joint; Applications of matrices to solution of simple
business and economic problems
Unit
II: Differential Calculus Marks: 10
Mathematical
functions and their types – linear, quadratic, polynomial; Concepts of limit
and continuity of a function; Concept of differentiation; Rules of
differentiation – simple standard forms. Applications of differentiation –
elasticity of demand and supply; Maxima and Minima of functions (involving
second or third order derivatives) relating to cost, revenue and profit.
Unit
III: Basic Mathematics of Finance Marks:
12
Simple and
compound interest Rates of interest – nominal, effective and continuous – their
inter relationships; Compounding and discounting of a sum using different types
of rates.
Part
– B: Business Statistics (37L+2T) Marks: 16
Unit
I: Uni-variate Analysis
Measures of
Central Tendency including arithmetic mean, geometric mean and harmonic mean:
properties and applications; mode and median. Partition values - quartiles,
deciles, and percentiles.
Measures of Variation: absolute and relative. Range, quartile
deviation and mean deviation; Variance and Standard deviation: calculation and
properties.
Unit
II: Bi-variate Analysis Marks: 16
Simple Linear
Correlation Analysis: Meaning, and measurement. Karl Pearson's co-efficient and
Spearman’s rank correlation.
Simple Linear
Regression Analysis: Regression equations and estimation. Relationship between
correlation and regression coefficients.
Unit
III: Time-based Data: Index Numbers and Time-Series Analysis Marks: 16
Meaning and uses of index numbers; Construction of index numbers:
Aggregative and average of relatives – simple and weighted, Tests of adequacy
of index numbers, Construction of consumer price indices.
Components of time series; additive and multiplicative models;
Trend analysis: Finding trend by moving average method and Fitting of linear
trend line using principle of least squares.
Suggested
Readings:
a) Mizrahi and
John Sullivan. Mathematics for Business
and Social Sciences. Wiley and Sons.
b) Budnick, P. Applied Mathematics. McGraw Hill
Publishing Co.
c) N. D. Vohra, Business Mathematics and Statistics,
McGraw Hill Education (India) Pvt Ltd
d) J.K. Thukral,
Mathematics for Business Studies, Mayur
Publications
e) J. K. Singh, Business Mathematics, Himalaya
Publishing House.
f) J. K. Sharma,
Business Statistics, Pearson Education.
g) S.C. Gupta, Fundamentals of Statistics, Himalaya
Publishing House.
h) S.P. Gupta
and Archana Gupta, Elementary Statistics,
Sultan Chand and Sons, NewDelhi.
i)
Richard Levin and David S. Rubin, Statistics for Management, Prentice Hall of India, New Delhi.
j)
M.R. Spiegel, Theory and
Problems of Statistics, Schaum’s Outlines Series, McGraw Hill Publishing Co.
(Note: Latest edition of text books may be used.)
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