B.Com. (Hons.)(CBCS)
Semester – III
Paper – G 303
BUSINESS STATISTICS
Full Marks: 100
(Internal Assessment 20 + 80
End-Term)
Lectures: 45, Practical: 26
Hours
Tutorial: 7 Hrs
Objective: The objective of this course is to familiarise students
with the basic statistical tools used for managerial decision-making.
Unit 1
Statistical Data and Descriptive Statistics
7 L + 1 T
a. Nature and Classification of data: univariate, bivariate and
multivariate data; time-series and cross-sectional data.
b. Measures of Central Tendency i. Mathematical averages including
arithmetic mean, geometric mean and harmonic mean. Properties and applications.
ii. Positional Averages Mode and Median (and other partition values including
quartiles, deciles, and percentiles) (including graphic determination)
c. Measures of Variation: absolute and relative. Range, quartile
deviation, mean deviation, standard deviation, and their coefficients,
Properties of standard deviation/variance.
d. Skewness: Meaning, Measurement using Karl Pearson and Bowley’s
measures; Concept of Kurtosis. Marks:10
Unit 2
Probability and Probability Distributions
9 L + 1 T
a. Theory of Probability. Approaches to the calculation of
probability; Calculation of event probabilities. Addition and multiplication
laws of probability (Proof not required); Conditional probability and Bayes’
Theorem (Proof not required)
b. Expectation and variance of a random variable.
c. Probability distributions:
i. Binomial distribution:
Probability distribution function, Constants, Shape, Fitting of binomial
distribution.
ii. Poisson distribution:
Probability function, (including Poisson approximation to binomial
distribution), Constants, Fitting of Poisson distribution.
iii. Normal distribution:
Probability distribution function, Properties of normal curve, Calculation of
probabilities. Marks:16
Unit 3
Simple Correlation and Regression Analysis
8 L + 1 T
a. Correlation Analysis: Meaning of Correlation: simple, multiple
and partial; linear and non-linear, Correlation and Causation, Scatter diagram,
Pearson’s co-efficient of correlation; calculation and properties (Proof not
required). Correlation and Probable error; Rank Correlation
b. Regression Analysis: Principle of least squares and regression
lines, Regression equations and estimation; Properties of regression
coefficients; Relationship between Correlation and Regression coefficients;
Standard Error of Estimate and its use in interpreting the results. Marks:
16
Unit 4
Index Numbers
8 L + 1 T
Meaning and uses of index numbers;
Construction of index numbers: fixed and chain base: univariate and composite.
Aggregative and average of relatives – simple and weighted Tests of adequacy of
index numbers, Base shifting, splicing and deflating. Problems in the
construction of index numbers; Construction of consumer price indices:
Important share price indices, including BSE SENSEX and NSE NIFTY. Marks: 16
Unit 5
Time Series Analysis
8 L + 1 T
Components of time series;
Additive and multiplicative models; Trend analysis: Fitting of trend line using
principle of least squares – linear, second degree parabola and exponential.
Conversion of annual linear trend equation to quarterly/monthly basis and
vice-versa; Moving averages; Seasonal variations: Calculation of Seasonal
Indices using Simple averages, Ratio-to-trend, and Ratio-to-moving averages
methods. Uses of Seasonal Indices. Marks: 14
UNIT 6
Sampling Concepts, Sampling Distributions and Estimation
5 L + 1 T
Sampling: Populations and
samples, Parameters and Statistics, Descriptive and inferential statistics;
Sampling methods (including Simple Random sampling, Stratified sampling,
Systematic sampling, Judgement sampling, and Convenience sampling) Concept of
Sampling distributions and Theory of Estimation: Point and Interval estimation
of means (large samples) and proportions.
Marks: 8
Practical Lab 26
The students will be
familiarized with software (Spreadsheet and/or SPSS) and the statisticaland
other functions contained therein related to formation of frequency
distributions andcalculation of averages, measures of Dispersion and variation,
correlation and regression coefficient.
Note:
1. There shall be 4 Credit Hrs. for Lectures + one Credit hr. (Two
Practical Periods per week per batch) for Practical Lab + one credit Hr for
Tutorials (per group)
2. Latest edition of text books may be used.
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