Credits : 3, Lecture Hours: 48
Statistical Methods Syllabus | MBS First Semester
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.
Unit 2: 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 the central limit theorem
- Estimation theory,
- criteria of a 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 tests,
- 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 correlations,
- 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.
