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M-SC in Biostatistics And Epidemiology at SRM Institute of Science and Technology
Chengalpattu, Tamil Nadu
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About the Specialization
What is Biostatistics and Epidemiology at SRM Institute of Science and Technology Chengalpattu?
This M.Sc Biostatistics and Epidemiology program at SRM Institute of Science and Technology focuses on equipping students with advanced statistical and epidemiological methods crucial for public health and clinical research. The Indian healthcare sector is rapidly expanding, creating a significant demand for professionals skilled in analyzing complex health data. This program differentiates itself by integrating theoretical knowledge with practical applications, addressing critical public health challenges relevant to India.
Who Should Apply?
This program is ideal for science graduates from diverse backgrounds including Statistics, Biosciences, and Medical fields, seeking entry into data-driven health roles. It also suits working professionals in healthcare or pharmaceuticals looking to upskill in quantitative analysis, and career changers transitioning into the rapidly evolving healthcare analytics and research industry in India. A strong analytical aptitude and an interest in public health are key prerequisites.
Why Choose This Course?
Graduates of this program can expect promising career paths as Biostatisticians, Epidemiologists, Clinical Data Managers, or Research Analysts in India. Entry-level salaries typically range from INR 4-7 LPA, with experienced professionals earning INR 10-20+ LPA in pharmaceutical companies, CROs, public health organizations, and academic institutions. The program also aligns with certifications in statistical software and research ethics, enhancing professional growth trajectories in Indian and global markets.
Student Success Practices
Foundation Stage
Master Core Statistical Software- (Semester 1-2)
Dedicate time in Semesters 1 and 2 to achieve proficiency in statistical software like R and SPSS. Utilize online tutorials, practice datasets, and participate in coding challenges to reinforce learning and build a strong foundation for data analysis tasks.
Tools & Resources
Coursera/edX courses on R/SPSS, SRMIST Statistical Software Labs, Kaggle datasets
Career Connection
Strong software skills are non-negotiable for biostatisticians and epidemiologists, directly impacting employability in data analysis roles in pharmaceutical and public health sectors.
Build a Strong Mathematical & Probabilistic Base- (Semester 1-2)
Regularly review and practice Bio Mathematics and Probability & Distribution Theory concepts. Form study groups to solve complex problems and ensure a deep understanding, which is critical for advanced biostatistical methods.
Tools & Resources
Textbooks on Biomathematics, Khan Academy, Peer study groups
Career Connection
A solid theoretical foundation prevents superficial analysis and enables innovative problem-solving in research, which is valued in advanced research and development roles.
Engage in Public Health Discussions- (Semester 1-2)
Actively participate in departmental seminars, webinars, and discussions related to public health and epidemiology. Stay updated with current health issues and research findings, enhancing your understanding of real-world applications.
Tools & Resources
WHO/ICMR publications, Public Health Foundation of India (PHFI) events, Departmental colloquia
Career Connection
This broadens your perspective, aids in identifying research gaps, and prepares you for roles that require a comprehensive understanding of health systems and policies in India.
Intermediate Stage
Seek Practical Research Exposure- (Semester 3-4)
Proactively seek out research projects with faculty or apply for internships in local hospitals, NGOs, or health research institutes during semester breaks. Focus on applying learned epidemiological and statistical methods to real datasets.
Tools & Resources
SRMIST Research Portal, Local hospitals'''' research departments, NGOs like Public Health Foundation of India
Career Connection
This practical experience builds a portfolio, enhances problem-solving skills, and provides crucial networking opportunities for future placements in the Indian healthcare industry.
Develop Advanced Data Visualization Skills- (Semester 3-4)
Beyond basic charting, learn to create compelling and informative data visualizations using specialized tools. Effective communication of complex statistical findings is crucial in public health and research.
Tools & Resources
Tableau Public, Power BI, ggplot2 in R
Career Connection
Visual communication skills are highly valued in research presentation, grant applications, and roles requiring clear reporting to non-technical stakeholders in India and globally.
Participate in Health Data Hackathons/Competitions- (Semester 3-4)
Engage in health-focused hackathons or data science competitions. These platforms provide opportunities to work on challenging datasets, collaborate with peers, and showcase your analytical capabilities under time pressure.
Tools & Resources
Kaggle, Analytics Vidhya competitions, Local university hackathon announcements
Career Connection
Winning or even participating in such events demonstrates initiative, practical skill, and resilience, which are attractive qualities for recruiters in the competitive Indian job market.
Advanced Stage
Specialize through Electives and Project Work- (Semester 3-4)
Strategically choose electives that align with your career interests (e.g., Clinical Trials, Environmental Biostatistics, Survival Analysis). Dedicate significant effort to your Project Work, aiming for a publishable quality thesis.
Tools & Resources
Faculty advisors, Research journals, Mendeley/Zotero for referencing
Career Connection
Specialization makes you a niche expert, and a strong project can serve as a powerful resume builder and a topic for job interviews, especially for research-oriented roles or PhD aspirations in India.
Refine Presentation and Communication Skills- (Semester 3-4)
Regularly practice presenting your research findings and statistical interpretations in a clear, concise, and engaging manner. Seek feedback from professors and peers on your technical communication skills.
Tools & Resources
Toastmasters clubs (if available), Departmental presentation sessions, Online public speaking tutorials
Career Connection
Effective communication is vital for consulting, research collaborations, and leadership roles. It significantly boosts your chances during interviews and in your professional career.
Network and Attend Industry Conferences- (Semester 3-4)
Actively network with professionals in the biostatistics and epidemiology fields. Attend national and international conferences (e.g., Indian Public Health Association, International Biometric Society) to stay updated and explore job opportunities.
Tools & Resources
LinkedIn, Professional associations websites, Conference brochures
Career Connection
Networking opens doors to hidden job markets, mentorship opportunities, and collaborative ventures, which are invaluable for career advancement in India''''s dynamic healthcare landscape.
Program Structure and Curriculum
Eligibility:
- B.Sc. degree in Statistics/Mathematics/Computer Science/Bioinformatics/Microbiology/Biochemistry/Biotechnology/Biology/Botany/Zoology/Physics/Chemistry, or B.A. Economics, or B.E./B.Tech. Biotechnology/Bioinformatics or MBBS/BDS/BPT/B.Pharm/B.Sc. Nursing/B.V.Sc. or equivalent examination passed from recognized universities, with a minimum aggregate of 50%.
Duration: 2 years (4 semesters)
Credits: 78 Credits
Assessment: Internal: Not explicitly defined in syllabus document, External: Not explicitly defined in syllabus document
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MB2101 | Bio Mathematics and Biostatistics | Core | 4 | Linear Algebra, Calculus, Differential Equations, Matrix Algebra, Probability Concepts |
| MB2102 | Introduction to Biostatistics and Data Management | Core | 4 | Basic Statistical Concepts, Data Collection Methods, Descriptive Statistics, Data Visualization, Data Cleaning and Transformation |
| MB2103 | Computer Application in Biostatistics | Core | 4 | Introduction to Computers, Operating Systems, MS Office Applications, Data Entry and Spreadsheet Management, Presentation Tools |
| MB2104 | Probability and Distribution Theory | Core | 4 | Basic Probability Theory, Random Variables, Probability Distributions, Expected Values, Central Limit Theorem |
| MB2105 | Introduction to Public Health | Core | 3 | Concepts of Public Health, Health Determinants, Disease Prevention, Health Policies, Global Health Issues |
| MB21L1 | Computer Applications Lab | Lab | 2 | MS Word for Documentation, MS Excel for Data Handling, MS PowerPoint for Presentations, Internet Browsing for Research, Basic Data Management |
| MB21L2 | Statistical Software Lab - I | Lab | 2 | Introduction to SPSS/R, Data Entry and Manipulation, Descriptive Statistics using Software, Graphical Representation of Data, Basic Inferential Statistics |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MB2106 | Statistical Inference | Core | 4 | Estimation Theory, Hypothesis Testing, Parametric Tests, Non-parametric Tests, ANOVA and ANCOVA |
| MB2107 | Epidemiology Methods – I | Core | 4 | Measures of Disease Occurrence, Study Designs in Epidemiology, Bias and Confounding, Effect Modification, Public Health Surveillance |
| MB2108 | Multivariate Biostatistics | Core | 4 | Multivariate Normal Distribution, Principal Component Analysis, Factor Analysis, Discriminant Analysis, Cluster Analysis |
| MB2109 | Research Methodology | Core | 3 | Research Design, Sampling Techniques, Data Collection Instruments, Ethics in Research, Report Writing |
| MB21E1 | Elective I | Elective | 3 | Demographic Measures, Population Dynamics, Health Economics Principles, Healthcare Financing, Economic Evaluation in Health |
| MB21L3 | Statistical Software Lab – II | Lab | 2 | Regression Analysis in R/SPSS, ANOVA using Software, Non-parametric Tests, Multivariate Data Analysis, Interpretation of Statistical Outputs |
| MB21L4 | Epidemiology Lab | Lab | 2 | Calculating Disease Measures, Data Analysis for Epidemiological Studies, Case Study Analysis, Introduction to EpiInfo, Interpretation of Epidemiological Data |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MB2110 | Advanced Biostatistics | Core | 4 | Generalized Linear Models, Logistic Regression, Poisson Regression, Mixed Models, Time Series Analysis |
| MB2111 | Epidemiology Methods – II | Core | 4 | Screening and Diagnostic Tests, Communicable Disease Epidemiology, Non-Communicable Disease Epidemiology, Environmental Epidemiology, Molecular Epidemiology |
| MB2112 | Design of Experiments | Core | 4 | Basic Principles of DOE, Completely Randomized Design, Randomized Block Design, Factorial Experiments, Split-Plot Designs |
| MB2113 | Clinical Trials | Core | 3 | Phases of Clinical Trials, Trial Design, Randomization and Blinding, Sample Size Calculation, Regulatory Affairs |
| MB21E2 | Elective II | Elective | 3 | Survival Data Analysis, Kaplan-Meier Estimator, Cox Proportional Hazards Model, Genetic Linkage Analysis, Genomic Data Interpretation |
| MB21P1 | Project Work – I (Internal Evaluation) | Project | 6 | Problem Identification, Literature Review, Methodology Design, Data Collection Planning, Interim Report Writing |
| MB21I1 | Internship (2 weeks) | Internship | 1 | Practical Data Application, Industry Exposure, Real-world Problem Solving, Professional Networking, Skill Enhancement |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MB2114 | Categorical Data Analysis | Core | 4 | Contingency Tables, Chi-Square Tests, Logistic Regression for Categorical Outcomes, Log-linear Models, Generalized Estimating Equations |
| MB2115 | Statistical Quality Control | Core | 4 | Quality Control Concepts, Control Charts, Acceptance Sampling, Process Capability Analysis, Total Quality Management |
| MB21E3 | Elective III | Elective | 3 | Environmental Health Risk Assessment, Spatial Epidemiology, Statistical Methods for Drug Development, Adaptive Trial Designs, Pharmacoeconomics |
| MB21P2 | Project Work – II (External Evaluation) | Project | 10 | Advanced Data Analysis, Model Building and Validation, Result Interpretation, Dissertation Writing, Oral Presentation and Defense |
