M.Sc. Statistics
M.Sc. Statistics is a two year full time Master’s Programme at MIT-WPU, where we transform data into insights and empower you to shape the future with numbers. Designed for aspiring statisticians and data scientists, our comprehensive program equips you with the skills and knowledge needed to thrive in a data-driven world.
Our programme covers a wide spectrum of statistical theories, methodologies, and their practical applications. Dive into courses such as Probability Theory, Regression Analysis, Multivariate Statistics, Time Series Analysis, Machine Learning, and more. Learn from esteemed faculty members who are industry experts and passionate educators, guiding you through complex statistical concepts and their real-world applications. Gain practical experience through projects, and internships with leading organisations. Apply your theoretical knowledge to solve real challenges and make data-driven decisions.
Last Date to Apply : 17 May 2025
M.Sc. Statistics
Scholarship for AY 2025-26 | Graduation Aggregate Score | XII Aggregate Score |
Dr. Vishwanath Karad Scholarship (100%) | 85 & Above | 85 & Above |
MIT-WPU Scholarship I (50%) | 80 & Above | 80 & Above |
MIT-WPU Scholarship II (25%) | 75 & Above | 75 & Above |
Note: Student will have to qualify both the criteria i.e. Graduation Aggregate Score and 12th Aggregate Score for availing the scholarship
*Terms & Conditions apply:- All Scholarships are awarded on a First Come First Serve basis. All Scholarships are awarded as fee adjustments.
- To continue the scholarship for the entire duration of the programme, a minimum level of the academic score has to be maintained at an 8 CGPA across all semesters, attendance is to be maintained at a minimum of 80 percent and there should be no disciplinary action against the student.
For more detailed information visit our website: https://mitwpu.edu.in/scholarships
Minimum 50% aggregate score in 3/4-year graduation or equivalent from Govt. Approved Institution in relevant programme. Graduation must be in B.Sc/B.Sc.(Hons) in Statistics, Data Science, Machine Learning, or equivalent degree (B.E./B.Tech./B.Sc. Agri/ B.Sc. Computer Science). The candidates other than B.Sc. Statistics must have Statistics as one of the regular subjects in their undergraduate programme (at least 45% in case of candidates of Reserved Class categories belonging to Maharashtra State only).
Selection ProcessThe selection process for M.Sc. Statistics is based on MIT-WPU CET Entrance Examination 2025 & Personal Interaction.
(The exact date and time of the online Examination and Personal Interaction will be communicated to the candidate once scheduled.)
*Note: MIT-WPU retains the right to make changes to any published schedule. Any other criterion declared from time to time by the appropriate authority as defined under the Act.

- Highly qualified faculty, with a strong track record of research and publication
- Workshops for hands-on experience in software such as R, SAS, Python, HADOOP, SQL, SPSS
- Guest lectures, seminars, and workshops by eminent corporate leaders
- MOOCs, skill enhancement and interdisciplinary courses for holistic development
- Industry and Teaching Internship
- Dedicated Centre for Industry-Academia Partnerships to support students for internships and job placements
- MIT-WPU Technology Business Incubator (TBI) to support early-stage entrepreneurs, and students through funding, mentoring, and network connection
- Disciplinary Knowledge: Apply statistics to solve problems in economics, social sciences, science, engineering, and technology
- Critical Thinking: Identify, analyse, and solve relevant problems using domain-specific skills
- Reflective Thinking: Use modern tools and techniques, contributing to society's understanding of maths global impact
- Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions
- Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex statistics activities with an understanding of the limitations
- Problem-Solving: Graduates will design mathematics models to solve problems with appropriate consideration of public health and safety, cultural and societal and environmental considerations