M.Sc. Applied Statistics
Programme Overview
M.Sc. Applied 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 programme 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 the robust curriculum that incorporates 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.
Duration & Fees
Duration
2 Years
Applications Open for 2026
Fee Per Year
₹ 1,10,000
Scholarship
| Scholarship for AY 2025-26 | Graduation Score | XII Score |
|---|---|---|
|
Dr. Vishwanath Karad Scholarship |
85 & Above |
85 & Above |
|
MIT-WPU Scholarship I |
80 & Above |
80 & Above |
|
MIT-WPU Scholarship II |
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, with no live backlogs in any subject/programme and no semester break, and there should be no disciplinary action against the student.
For more detailed information visit our website: https://mitwpu.edu.in/scholarships
Eligibility
Minimum 50% aggregate marks in 3/4-year graduation degree in B. Sc. /B.Sc.(Hons) in Mathematics/ Statistics/ Data Science/ Machine Learning or equivalent degree or B.E./B.Tech./B.Sc. Agri/ B.Sc. Computer Science. Candidates with degrees other than B.Sc. Statistics must have studied Statistics as a regular subject in their undergraduate programme from a UGC-approved institution/university or its equivalent (minimum 45% for candidates belonging to the Reserved Category from Maharashtra State).
Selection Process
Admission will be based on the MIT-WPU CET 2026 Entrance Examination and the Personal Interaction (PI) score, conducted by the University as per the prescribed schedule
Programme Highlights
- 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
Programme Structure
| Sr. No | Course Name/Course Title | Course Type | Credits |
|---|---|---|---|
|
1 |
Linear Algebra | PF | 3 |
|
2 |
Distribution Theory | PF | 3 |
|
3 |
R Programming + SQL | PM | 2 |
|
4 |
Research Methodology | PM | 4 |
|
5 |
Sampling | PM | 3 |
|
6 |
Program Elective - 01 | PE | 4 |
|
7 |
Scientific Studies of Mind, Matter, Spirit and Consciousness | UC | 2 |
|
8 |
Yoga | UC | 1 |
|
Total Credits |
22 | ||
| Sr. No | Course Name/Course Title | Course Type | Credits |
|---|---|---|---|
|
1 |
Multivariate Analysis | PM | 4 |
|
2 |
Multivariate and Regression Lab | PM | 1 |
|
3 |
Python Lab | PM | 1 |
|
4 |
Regression Analysis | PM | 3 |
|
5 |
Statistical Computing | PM | 4 |
|
6 |
Statistical Inference | PM | 3 |
|
7 |
Program Elective - 02 | PE | 4 |
|
8 |
Peace - II | UC | 2 |
|
Total Credits |
22 | ||
| Sr. No | Course Name/Course Title | Course Type | Credits |
|---|---|---|---|
|
1 |
Clinical Trial | PM | 4 |
|
2 |
Design of Experiment | PM | 4 |
|
3 |
Lab on Time Series analysis and Project | PM | 2 |
|
4 |
Time Series Analysis | PM | 4 |
|
5 |
Program Elective - 03 | PE | 4 |
|
6 |
On job Training (OJT)/Internship | PR | 4 |
|
Total Credits |
22 | ||
| Sr. No | Course Name/Course Title | Course Type | Credits |
|---|---|---|---|
|
1 |
Program Elective-04 | PM | 4 |
|
2 |
Exploratory Analysis | PM | 2 |
|
3 |
Project / Industrial Internship | PR | 16 |
|
Total Credits |
22 | ||
Career Prospects
Analytics Consultants
Analytics Programmers
Biostatistician
Business advisors and strategists
Business Analysts
Clinical data analysts
Data analysts
Data scientists
Management Analysts
Market research analysts
Programme Outcomes
- 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
FAQs
Graduates gain advanced skills in statistical theory, data analysis, statistical computing, and interpretation of complex data sets, preparing them for roles in industry, research, and academia.
Absolutely. The curriculum integrates applications of statistics in fields like data science, economics, finance, life sciences, and social sciences.
Yes, the department regularly organises guest lectures, seminars, and workshops with industry experts and academicians.
MIT-WPU offers scholarships for eligible students based on merit and other criteria. For more detailed information visit our website: https://mitwpu.edu.in/scholarships
admissions@mitwpu.edu.in
