Areas/Courses

The department offers a diverse range of courses designed to provide a strong foundation in statistics and its applications across various fields. Our curriculum includes:

Basic Statistics: Integral to virtually every program, this course establishes the fundamental principles essential for research endeavors.

Probability Distributions: Explore the nuances of probability distributions, vital in understanding uncertainty and randomness in data.

Sampling Methods: Understand the methodologies involved in obtaining representative samples from populations.

Regression and Correlation Analysis: Dive into predictive modeling and the relationship between variables through regression and correlation techniques.

Time Series Data Analysis: Learn methods to analyze and interpret data collected over time, crucial in various domains such as economics, finance, and environmental studies.

Experimental Design: Gain insights into designing experiments to validate hypotheses and draw meaningful conclusions.

Biostatistics: Explore statistical methods applied in biological and health sciences for data analysis and inference.

Data Analytics and Business Intelligence: Extract insights from data using mining, visualization, and predictive analytics.

Computational Statistics: Apply computational methods using languages such as R and Python to efficiently solve statistical problems.

Additionally, our programs emphasize the development of computational skills through exposure to various programming languages, software, and relevant packages, enhancing proficiency in handling and analyzing data.