Master of Science (Applied Statistics)

Real Analysis, Calculus and Geometry

Probability and Probability Distributions

Survey Sampling and Design of Experiments-I

Statistical Quality Control and Time Series Analysis

Introduction to R Software

Statistical Inference

Applied Regression Analysis

Multivariate Analysis

Epidemiology and Clinical Trials

Survey Sampling and Design of Experiments-II

Classical and Bayesian Inference

Linear Algebra and Multivariable Calculus

Research Methodology

Data Analysis with Python

Categorical and Survival Analysis

Introduction to Machine Learning

Operations Research (elective)

Stochastic Processes (elective)

Statistical Computing using R-I (Lab)

Statistical Computing using R-II (Lab)

Statistical Computing using R-III (Lab)

Data Analysis with Python Lab

Statistical Computing using R-IV (Lab)

Project/Dissertation (elective)