Master of Science (M.Sc) in Statistics course is offered at Tribhuvan University Central Department of Statistics. It is a two-year, 4-semester program and a postgraduate degree emphasizing collecting and interpreting statistics.
Social sciences, finance, and econometrics are all covered as potential areas for gathering statistical data. The degree requires a solid mathematical background, with equal attention to practical math like algebra and more advanced subjects like multi-variable calculus. The program also covers the design side of statistics, including subjects like survey sampling and experiment implementation.
Degree holders with an MSc in Statistics have various job options. Especially in the public sector, there is a lack of qualified statisticians, so finding rewarding work that allows a choice of projects is generally possible. Graduates with an MSc in Statistics may pursue the social sciences side of statistics. They might work for a consulting company in this field, analyzing people’s preferences and tendencies. They may otherwise choose to work in finance.
M.Sc/MA Statistics Entrance Examination
- The weightage of the entrance examination will be 100 full marks, and the duration will be 2 hours. Questions are asked according to the B.Sc/BA Statistics syllabus prescribed by the committee.
- The questions will be Objective or Multiple choice questions (MCQs). Each question will carry 1 (one) weightage.
- 35% marks must be obtained to pass the entrance examination.
M.Sc. Statistics postgraduates are lucratively hired at consultancies, in roles that require analyzing people’s preferences and tendencies. Finance, Marketing, and Data Metrics are other such areas of employment.
The graduates can work in various positions such as:
- Data Scientist
- Data Analyst
- Analytics Consultant
- Senior Business Analyst
- SAS Programmer
- Statistical Analyst
- Analytics Manager
- Senior Statistician
- Mathematical Demography Probability Distribution (Old)
- Sampling Theory
- Design of Experiments
- Quality Control and Reliability
- Meta Analysis
- Non-parametric and Categorical Data Modeling