Programme Structure: 

The programme offers specializations in :

  1. Biostatistics and Data Analysis.
  2. Industrial Statistics and Operation Research
  3. Financial and Actuarial Statistics
  4. Computational Statistics
  • The courses taken in Semester III are based on the choice of specialization and the relevant optional courses offered in that specialization
  • The programme also includes some pre-requisite courses
  • The students will be required to undertake an internship of two months. This is during the month of
    May and June after completion of the first two semesters. The students undertake their Dissertation as part of the programme in Semester IV. Other than the regular credit course, Institute will also conduct some tutorial and workshop training, which will be a non-credit course
    but forms a part of the programme.
Semester I
Sr. No. Subject Credits
1. Probability and Distribution Theory 4
2. Sampling and Estimation Theory 4
3. Real Analysis 4
4. Statistical and Mathematical Models 4
5. Regression Techniques 4
  Total 20
Semester II
Sr. No. Subject Credits
1. Statistical Inference 4
2. Linear Algebra And Linear Models 4
3. Design Of Experiments 4
4. Multivariate Analysis 4
5. Programming and Statistical Computing (excel minor addon, R, SPSS, SAS, Python) 4
6. Internships (Primary/secondary data) 2
  Total 22
Semester III
Sr. No. Subject Credits
1. Stochastic Processes and Applications 4
2.  Statistical Methods for Quality Control 4
3. Time Series Analysis 3
4. Specialization Course-1 3
5. Specialization Course-2 3
6. Specialization Course-3 3
7. Scientific writing 1
  Total 21
Semester IV
Sr. No. Subject Credits
1. Seminar 1
2. Data Analytics 4
3. Specialization Course-4 4
4. Specialization Course-5 4
5. Industry Project In Specialization/ Dissertation  4
  Total 17

Note: Theory and practical credits depends upon chosen specialization

  • Depending upon the strength of the students we will be offering specialization in Biostatistics and Data Analysis, Industrial Statistics and Operations Research, Financial and Actuarial Statistics, Computational Statistics.

Credits: 80


Students have to choose one of the following specializations in the semester III: 5 courses/specialization

Course code Specialization in subject
S1 Biostatistics and Data Analysis
S2 Industrial Statistics and Operations Research
S3 Financial and Actuarial Statistics
S4 Computational Statistics

Note: For semester three, students need to choose any five courses per specialization.

The Institutional committee may decide

(i) To offer two modules, where courses from these five modules will be merged or

(ii) To offer module specific courses as optional/elective courses or

(iii) To offer module specific/optional/elective courses as compulsory courses.

List of elective subjects:

 Elective  subject
E1 Empirical Processes
E2 Sequential Analysis
E3 Nonparametric Inference
E4 Discrete Data Analysis
E5 Stochastic Models in Epidemiology
E6 Longitudinal Data Analysis
E7 Directional Data Analysis
E8 Big data analytics
E9 Machine learning and AI
E10 Machine learning
E11 AI and algorithm
The Director of the Institute may introduce additional optional courses on recommendations of the Institutional Committee. The syllabus of the optional courses will be prepared by the concerned teacher and will be flexible to accommodate new developments in that area. Whenever such an optional course is floated, the concerned syllabus will be discussed and approved in the Institutional committee.