Program Outcomes
The department of Statistics has updated the syllabus of Masters Programme in consonance with spirit of New Education Policy-2020.The courses of Master Degree Programme (MDP) in Statistics has been designed encompassing academic flexibility, experiential learning and skills of use of modern and advance computational tools. The department apart from academic learning  also focus on the holistic growth of the students. Upon completion of the programme, students will acquire the domain knowledge of the Statistics majorly focusing on the statistical solutions to the real life problems which will open the avenues of employment and better human resource to contribute to the nation development. Students of the Masters programme at the end of course will :

Solid Theoretical Foundation: Understand core principles and theories of statistics including probability theory, statistical inference, regression analysis, Sample surveys , design of experiments , Optimization techniques and multivariate analysis.

Data Analysis Skills: Ability to collect, manage, analyze, and interpret data using appropriate statistical techniques and software tools (such as R, Python, MatLab and SPSS).

Statistical Modeling and Inference: Proficiency in applying advanced statistical models and methods to solve real-world problems, including hypothesis testing, experimental design, time series analysis, and Bayesian statistics.

Mathematical Proficiency: Strong mathematical foundation, including Mathematical Analysis, linear algebra, and mathematical statistics, necessary for understanding advanced statistical concepts.

Critical Thinking and Problem-Solving: Develop analytical and critical thinking skills to evaluate statistical methods, interpret results, and make data-driven decisions.

Communication Skills: Effectively communicate statistical findings and interpretations to both technical and non-technical audiences through reports, presentations, and visualizations.

Ethical and Professional Standards: Understand and adhere to ethical standards in statistical practice, including issues related to confidentiality, bias, and reproducibility of research findings.

Research and Collaboration: Ability to conduct independent research in statistics, including formulating research questions, designing studies, and analyzing data, as well as collaborating with multidisciplinary teams.

Continuous Learning and Professional Development: Commitment to lifelong learning, staying current with advances in statistical methods and technologies, and participating in professional development activities.

Application in Various Fields: Apply statistical methods and techniques across different domains such as healthcare, finance, environmental science, social sciences, and engineering.