Ph.D. Statistics

Ph.D. program in Statistics offered by the Department of Statistics since 2010 gives scope to researchers to pursue research in both theoretical and applied domains. Within the span of ten years, 18 students have been awarded doctorate degree and currently 16 students are pursuing their doctoral program. The department is supported for research by the University Grants Commission (UGC) – Special Assistance Program (SAP) – DRS – I level for the thrust areas Stochastic Processes, Optimization Techniques and Multivariate Data Analysis. Faculty are active in research and publish papers in national and international journals. All the faculty members have successfully completed one or more funded research projects with support grant from UGC, DST in their fields of specialization. Apart from this, the department also collaborates with other departments of the university and also with reputed institutions across the country and overseas.

Focus Areas


of the program

Statistical Inference & Distribution Theory

Focuses on theoretical perspectives with a blend of real life applications in allied areas of statistics

Stochastic Modelling & Optimization Methods

Focuses on stochastic modelling using data driven approach

Biostatistics & Classification Techniques

Focuses on research problems pertaining to medical statistics

Reliability Theory and Survival Analysis, Bayesian Inference

Focuses on developing models that deals with engineering and medical framework.

Who can prefer this Course


Master’s degree in Statistics with a minimum of 55% marks. The entrance examination for admission to Ph.D. (Statistics) program will consist of 100 multiple choice questions on two parts.
Part-1: 50 questions on the topics of
Linear Algebra, Matrix Theory, Time Series Analysis, Statistical Quality Control, Econometrics, Demography-Vital Statistics, Operations Research.
Part-2: 50 questions on the topics of
Probability Theory, Distribution Theory, Theory of Estimation, Sampling Theory, Stochastic Processes, Testing of Statistical Hypotheses, Multivariate Analysis, Design of Experiments, Reliability Theory and Non Parametric Inference.

Current Curriculum

  • Course Content
  • Reference Book
  • Valuation Pattern

Previous Curriculum

  • Course Content
  • Reference Book
  • Valuation Pattern
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