MODULE 1
Mathematical basis for managerial decision making, Matrices, Functions linear,
quadratic exponential applications, Differentiation, Maxima & Minima Emphasis on cost
and revenue functions, Fundamentals of integration, Ratio and Proportion.
MODULE 2
Business Statistics and scope, Application of Statistics in Managerial Decisions making,
Definition of Statistics, Measures of Central tendency, dispersion, Skew ness & Kurtosis
-interpretation and business applications.
MODULE 3
Probability Theory-meaning and importance, Theorems of probability, conditional
probability, joint probability, Baye’s Theorem, Random variable, expectation and
variance of random variable, Probability distributions-binomial, Poisson, normal and
exponential with business application
MODULE 4
Decision Theory, Decision Tree, Decision making under certainty, uncertainty and risk,
Bayesian approach
MODULE 5
Sampling, sampling distributions, Introduction to central limit theorem Estimation,
confidence interval, Hypothesis testing -basic concept, Hypotheses testing for mean
and proportions for small and large samples, ANOVA ONE WAY AND TWO WAY,
NON parametric tests, Chi square, sign test, run test, median test rank sum test,
Kruskal Walkusm K.S test, Mann Whitney test.
MODULE 6
Index Numbers construction and application, Tests of consistency, Correlation analysis,
Methods of correlation analysis, Lag and lead in correlation, Multiple Correlation,
Regression analysis Linear and multiple regression, Introduction to regression model
building via SPSS, Introduction to time series- secular trend and applications
BOOKS RECOMMENDED
1. Mittal, Sathyaprasad and Pradeep Rao, Mathematics and Statistics for Management, HPH
2. Azel and Sounderpandian, Complete Business Statistics, TMH
3. JK Sharma, Business Statistics, Pearson
4. RS Bhardwaj, Mathematics for Economics and Business, EB
5. RP Hooda, Statistics for Business and Economics, McMillan
6. GC Beri, Business Statistics, TMH
7. BR Dey, Managerial Statistics, McMillan
Mathematical basis for managerial decision making, Matrices, Functions linear,
quadratic exponential applications, Differentiation, Maxima & Minima Emphasis on cost
and revenue functions, Fundamentals of integration, Ratio and Proportion.
MODULE 2
Business Statistics and scope, Application of Statistics in Managerial Decisions making,
Definition of Statistics, Measures of Central tendency, dispersion, Skew ness & Kurtosis
-interpretation and business applications.
MODULE 3
Probability Theory-meaning and importance, Theorems of probability, conditional
probability, joint probability, Baye’s Theorem, Random variable, expectation and
variance of random variable, Probability distributions-binomial, Poisson, normal and
exponential with business application
MODULE 4
Decision Theory, Decision Tree, Decision making under certainty, uncertainty and risk,
Bayesian approach
MODULE 5
Sampling, sampling distributions, Introduction to central limit theorem Estimation,
confidence interval, Hypothesis testing -basic concept, Hypotheses testing for mean
and proportions for small and large samples, ANOVA ONE WAY AND TWO WAY,
NON parametric tests, Chi square, sign test, run test, median test rank sum test,
Kruskal Walkusm K.S test, Mann Whitney test.
MODULE 6
Index Numbers construction and application, Tests of consistency, Correlation analysis,
Methods of correlation analysis, Lag and lead in correlation, Multiple Correlation,
Regression analysis Linear and multiple regression, Introduction to regression model
building via SPSS, Introduction to time series- secular trend and applications
BOOKS RECOMMENDED
1. Mittal, Sathyaprasad and Pradeep Rao, Mathematics and Statistics for Management, HPH
2. Azel and Sounderpandian, Complete Business Statistics, TMH
3. JK Sharma, Business Statistics, Pearson
4. RS Bhardwaj, Mathematics for Economics and Business, EB
5. RP Hooda, Statistics for Business and Economics, McMillan
6. GC Beri, Business Statistics, TMH
7. BR Dey, Managerial Statistics, McMillan
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