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PH-D in Statistics at Shri Shivaji Science College (Autonomous)
Amravati, Maharashtra
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About the Specialization
What is Statistics at Shri Shivaji Science College (Autonomous) Amravati?
This Ph.D. Statistics program at Shri Shivaji Science College, Amravati, affiliated with Sant Gadge Baba Amravati University, focuses on nurturing advanced research capabilities in statistical theory and its applications. It is designed to equip scholars with the rigorous analytical tools and methodologies required to address complex problems in diverse Indian industries. The program distinguishes itself by combining foundational coursework with in-depth research, contributing to knowledge in areas relevant to national data-driven initiatives.
Who Should Apply?
This program is ideal for postgraduate students with an M.A./M.Sc. in Statistics or related fields who aspire to a career in advanced research, academia, or data science. It also caters to working professionals in analytics or R&D sectors seeking to enhance their theoretical understanding and contribute significant research. Candidates must possess a strong analytical aptitude and a desire to delve deep into statistical problems, often with prerequisites like a valid PET score or national-level research fellowships.
Why Choose This Course?
Graduates of this program can expect to pursue esteemed career paths as research scientists, university professors, advanced data scientists, or statistical consultants in both public and private sectors across India. Entry-level Ph.D. salaries in academia typically range from INR 6-10 lakhs per annum, while industry roles can offer INR 8-15 lakhs, with significant growth trajectories. The program aligns with the growing demand for highly skilled statisticians in sectors like finance, healthcare, and IT, facilitating professional certifications like SAS or R programming proficiency.
Student Success Practices
Foundation Stage
Master Research Methodology Fundamentals- (Semester 1 (Coursework Phase))
Thoroughly engage with the Research Methodology coursework. Understand the nuances of research design, data collection techniques, and various statistical tools applicable across disciplines. Actively participate in discussions and seek clarifications from faculty.
Tools & Resources
SGBAU Ph.D. Coursework materials, Standard textbooks on Research Methodology (e.g., Kothari), Access to university library research databases
Career Connection
A strong grasp of research methodology is fundamental for any advanced statistical research, enabling sound problem formulation and valid conclusions, critical for academic and industry research roles.
Intensive Literature Review in Statistics- (Semester 1 (Coursework Phase))
For the ''''Review of Literature and Seminar'''' paper, conduct an exhaustive and critical review of existing statistical literature in your chosen area of research. Identify research gaps, conflicting findings, and potential avenues for your contribution. Present your findings effectively in seminars.
Tools & Resources
JSTOR, Scopus, Web of Science, Google Scholar, Indian Statistical Institute (ISI) journal archives
Career Connection
Developing strong literature review skills is crucial for thesis writing and staying current with cutting-edge statistical advancements, a highly valued skill in academia and R&D.
Build a Strong Rapport with Research Guide- (Semester 1-2)
Establish clear communication channels with your assigned research guide from the outset. Discuss your research interests, align on a potential problem statement, and regularly seek feedback on your progress. Be proactive in scheduling meetings.
Tools & Resources
Meeting schedules, Email communication, Research proposal drafts
Career Connection
A supportive guide-scholar relationship is paramount for successful Ph.D. completion, offering mentorship, networking opportunities, and guidance crucial for future career trajectory.
Intermediate Stage
Develop Advanced Statistical Programming Skills- (Year 2-3)
Beyond theoretical knowledge, acquire proficiency in statistical programming languages essential for implementing complex statistical models. Focus on data manipulation, analysis, and visualization in these environments.
Tools & Resources
R programming, Python (with NumPy, SciPy, Pandas, Scikit-learn), SAS/SPSS (if relevant to research area), Online courses (Coursera, NPTEL, edX), Practice datasets on Kaggle
Career Connection
Hands-on coding skills are indispensable for any modern data-intensive role, significantly enhancing employability in data science, analytics, and academic research positions.
Attend and Present at Conferences/Workshops- (Year 2-4)
Actively seek opportunities to attend national/international conferences and workshops in Statistics. Present your preliminary research findings or review work. This helps in gaining exposure, receiving feedback, and networking with peers and experts.
Tools & Resources
Indian Statistical Institute (ISI) conferences, Operational Research Society of India (ORSI) events, Departmental seminars, University travel grants
Career Connection
Presenting research builds communication skills and establishes your presence in the academic community, opening doors for collaborations and future academic/research roles.
Publish Research Papers in Peer-Reviewed Journals- (Year 2-5)
Work diligently towards publishing your research findings in reputable, peer-reviewed national and international journals. Start with review papers or smaller research contributions. Focus on clarity, rigor, and originality.
Tools & Resources
Scopus/Web of Science indexed journals in Statistics, Journal submission platforms (e.g., Elsevier, Springer), Reference management software (Mendeley, Zotero)
Career Connection
Publications are critical for academic promotions, securing research grants, and building a strong research profile, essential for a successful career in academia or advanced R&D.
Advanced Stage
Prepare for Comprehensive Viva-Voce and Thesis Defense- (Year 3-6 (leading to thesis submission))
As you approach thesis completion, prepare rigorously for your pre-synopsis seminar and final viva-voce. Anticipate questions, practice articulating your research contributions clearly, and defend your methodology and findings effectively.
Tools & Resources
Mock viva sessions with guide/department faculty, Practice presentations, Review of thesis content and key arguments
Career Connection
Successful defense is the culmination of your Ph.D. and a direct gateway to receiving your degree, which is a prerequisite for advanced positions.
Network Strategically for Post-Ph.D. Opportunities- (Year 3-6 (especially in the final year))
Leverage your academic network, conference contacts, and university alumni connections to explore post-doctoral fellowships, faculty positions, or industry research roles. Attend career fairs specifically for Ph.D. graduates.
Tools & Resources
LinkedIn, University placement cell (if applicable for Ph.D.), Professional bodies in Statistics (e.g., Indian Statistical Association)
Career Connection
Proactive networking is crucial for discovering hidden job markets and securing desirable positions that align with your specialized research expertise.
Refine Teaching and Mentorship Skills- (Throughout Ph.D. (as opportunities arise))
If pursuing an academic career, seek opportunities to assist professors, conduct tutorials, or mentor junior students. Develop effective pedagogical skills, as teaching experience is vital for faculty positions.
Tools & Resources
Departmental teaching assistantships, Pedagogical training workshops, Feedback from students and supervising faculty
Career Connection
Strong teaching and mentorship skills are essential for securing and excelling in academic roles, where educating the next generation of statisticians is a core responsibility.
Program Structure and Curriculum
Eligibility:
- Master''''s degree (M.A./M.Sc.) in Statistics/Applied Statistics/Mathematics with Statistics with at least 55% marks (50% for reserved categories) or an equivalent grade. Candidates must have qualified the Sant Gadge Baba Amravati University (SGBAU) Ph.D. Entrance Test (PET) or possess a valid score in UGC-NET/CSIR-NET/SET/GATE/M.Phil. in the relevant discipline.
Duration: Minimum 3 years (Full-time), Minimum 4 years (Part-time)
Credits: Minimum 8 credits (for coursework phase) Credits
Assessment: Internal: 30% (General University Norm for Coursework), External: 70% (General University Norm for Coursework)
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PHDRM-01 | Research Methodology | Core (Mandatory for all Ph.D. Scholars) | 4 | Introduction to Research and Scientific Methods, Formulation of Research Problem and Hypotheses, Research Design and Methods, Data Collection, Sampling, and Measurement, Data Analysis, Interpretation, and Reporting, Research Ethics and Intellectual Property Rights |
| PHDSLS-02 | Review of Literature and Seminar (Statistics) | Core (Discipline Specific Mandatory) | 4 | Identification of Research Gaps in Statistical Theory and Applications, Advanced Literature Search Techniques for Statistical Journals, Critical Analysis and Synthesis of Existing Statistical Methodologies, Academic Writing and Referencing for Statistical Research Papers, Preparation and Presentation of Research Proposals in Statistics, Ethical Considerations and Plagiarism in Statistical Research |
