Statistical Modeling - 24DS636 (2024-25)
Course Introduction
The website contains course contents of “Statistical Modeling” offered by Abhijith M S, PhD to Masters students pursuing M.Tech in Data Science, during the even semester of the academic year 2024-25.
Syllabus
(As given in the curriculum)
- Probability, Random Variables & Probability Distributions.
- Sampling, analysis of sample data-Empirical Distributions, Sampling from a Population Estimation, confidence intervals, point estimation–Maximum Likelihood, Probability mass functions, Modeling distributions, Hypothesis testing- Z, t, Chi-Square.
- ANOVA & Designs of Experiments - Single, Two factor ANOVA, Factorials ANOVA models.
- Linear least squares, Correlation & Regression Models-linear regression methods, Ridge regression, LASSO, univariate and Multivariate Linear Regression, probabilistic interpretation, Regularization, Logistic regression, locally weighted regression.
- Exploratory data analysis, Time series analysis, Analytical methods – ARIMA and SARIMA.
Evaluations: A Tentative Timeline
Best two marks out of three quizzes (Total = 20 marks)
Quiz-1 (10 marks): (January First week)
Quiz-2 (10 marks):(March First week)
Quiz-3 (10 marks):(April First week)
Assignments (Total = 30 marks)
Assignment-1 (10 marks):(Submission: End of January)
Assignment-2 (10 marks):(Submission: End of March)
Project Review - 1 (10 marks):(February second week)
Mid Sem (Total = 20 marks)
Mid-Semester Exam (20 marks):(Feb first week, as per Academic calender)
End Sem (Total = 30 marks)
End-Semester Project Presentation (20 marks):(April second week, as per Academic calender) \end{itemize}$
Contact: ms_abhijith@cb.amrita.edu