Credits: 3
Lecture Hours: 48
Course Objectives:
The course aims to impart knowledge and skills of statistical techniques ad their applications in solving business problems
Course Details:
Unit 1: Probability LH6
Concept and importance of probability, approaches to probability. Additive and multiplicative
theorems, conditional probability, Baye’s theorem and decision tree.
Unit2: Probability Distribution LH6
Discrete probability distribution: Binomial and Poisson, Continuous probability distribution:
Normal Distribution and their properties along with applications.
Unit 3: Sampling and Estimation LH6
Sampling techniques, sampling and non-sampling errors, sampling distribution, standard error,
application of standard error, concept of central limit theorem
Estimation theory, criteria of good estimator, point and interval estimate, relationship among
errors, risk and sample size, determination of sample size.
Unit 4: Testing of Hypothesis LH18
Meaning of hypothesis testing, types of error in hypothesis testing, critical region, one tailed
and two tailed test, Parametric Test: large sample test of mean and proportions, small sample
test of mean, paired t-test, test of significance of correlation coefficient, variance ratio test, one
way and two way Analysis of Variance (ANOVA), Non-parametric test: Chi-square test of
goodness of fit and independence of attributes, chi-square test for population variance.
Unit 5: Correlation and Regression Analysis LH12
Partial and multiple correlation , coefficient of determination , concept of linear and non-linear
regression , multiple regression equation , standard error of estimate for multiple regression,
test of regression model and regression coefficients, auto-correlation and multicollinearity ,
Residual analysis: Linearity of the regression model, Homoscedasticity , Normality of error.
Reference Books:
Richard I. Levin and David S. Rubin, Statistics for Management, Prentice Hall of India
S.C.Gupta, Fundamental of Statistics, Himalayan Publishing House
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