DA 222-O Introductory Theoretical & Applied Statistics 3:1 (January 2022)
Course Instructor: : Chiranjit Mukhopadhyay, Mgmt.
Course description: This is a graduate-level course on theoretical and applied statistics. This four-credit course will be offered in the January-April term as an elective course of the Data Science and Business Analytics (DSBA) M.Tech Online program.
Syllabus
Paradigms of statistical inference - sampling & posterior distributions. Frequentist point and interval estimation - UMVUE, MLE, SE & CI. Frequentist theory for testing statistical hypotheses – UMPT, UMPUT, LRT & p-values. Bayesian estimation, hypothesis testing & prediction. Applications in one and two sample problems for mean, variance and proportions. Tests for goodness-of-fit, homogeneity and independence. Simple and multiple linear regression analysis - modeling, estimation, general linear hypotheses testing and prediction. Multiple and partial correlation analysis.
Textbooks / References
- Casella George & Berger Roger L. Statistical Inference. Second Edition. Duxbury, Thomson Learning. 2001.
- Michael H. Kutner, Christopher J. Nachtsheim, John Neter & William Li, Applied Linear Statistical Models, McGraw-Hill International Edition, Fifth Edition, 2005.
- David Freedman, Robert Pisani & Roger Purves, Statistics, W. W. Norton & Company, 4th edition
Prerequisites: None
Grading:
- Assignments/Quizzes 40%
- Midterm 30%
- Final exam 30%.