RGU M.Sc Statistics FAQs
Ques. What is the eligibility criteria for M.Sc Statistics at RGU?
Ans. Candidates must have a 3-year B.Sc degree with minimum 45% marks in Statistics or 50% marks in Mathematics from a UGC-recognized university. SC/ST candidates get 5% relaxation. Candidates awaiting final semester results can also apply.
Ques. What is the total fees for the M.Sc Statistics programme?
Ans. The total fees for the 2-year programme is INR 12,700, which is highly affordable. This includes INR 6,180 for the first semester and INR 6,520 for subsequent semesters. A refundable security deposit of INR 1,100 is also collected. Hostel fees are separate and optional.
Ques. How is admission conducted for M.Sc Statistics at RGU?
Ans. Admissions are conducted through CUET-PG 2025 (20% of seats) and RGUCET 2025 (80% of seats). Candidates can apply through https://admissions.rgu.ac.in/. Merit lists are prepared based on entrance examination scores, and additional weightage is given to bonafide students from affiliated colleges and APST candidates.
Ques. What are the career prospects after completing M.Sc Statistics from RGU?
Ans. Graduates can pursue careers as Data Analysts, Statisticians, Research Associates, Quality Analysts, and Actuarial Analysts in government organizations, research institutions, IT companies, finance sector, and analytics firms. Many graduates also pursue PhD programmes at premier institutions. The median salary package is around INR 4-5 LPA.
Ques. Does RGU offer scholarships for M.Sc Statistics students?
Ans. Yes, RGU offers various scholarships through the National Scholarships Portal (NSP) including Post-Matric Scholarship for SC/ST students, Pre-Matric Scholarship for economically disadvantaged students, and university merit scholarships. Students can apply through https://scholarships.gov.in/ for central government schemes.
Ques. What is the curriculum structure of M.Sc Statistics at RGU?
Ans. The 2-year programme consists of 88 credits spread across 4 semesters. Semester I and II focus on core courses like Statistical Methods, Probability Theory, Distribution Theory, Statistical Inference, Multivariate Analysis, Linear Models, and Survey Sampling. Semester III includes Stochastic Processes, Large Sample Theory, Design of Experiments, and electives. Semester IV focuses on electives and a dissertation project. The curriculum emphasizes both theoretical knowledge and practical skills through programming in C, R, and Python.
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