Department of Statistics
About the Department
The Department of Statistics at Bharathiyar Arts and Science College for Women (Autonomous), Deviyakurichi is committed to providing quality education in Statistics through innovative teaching, practical learning, research, and skill development. As a department of an Autonomous College, it has the academic flexibility to design and enrich its curriculum in accordance with emerging developments in Statistics, Data Analytics, Statistical Computing, and related interdisciplinary fields.
The department provides students with a strong foundation in statistical theory, probability, statistical inference, data analysis, statistical modelling, research methodology, and computational techniques. Equal emphasis is given to conceptual understanding and practical application, enabling students to apply statistical methods to real-world problems.
The department promotes an active learning environment through classroom teaching, laboratory-based training, student projects, seminars, workshops, guest lectures, internships, and research-oriented activities. Students are encouraged to develop analytical thinking, problem-solving abilities, computational skills, and evidence-based decision-making capabilities.
With dedicated faculty and a student-centred academic environment, the department strives to prepare graduates for higher education, research, competitive examinations, and diverse career opportunities in the rapidly expanding data-driven economy.
Academic Highlights
Autonomous Curriculum
As part of an autonomous institution, the department has the flexibility to enrich its curriculum with updated concepts, emerging technologies, practical components, skill-based courses, and interdisciplinary learning in response to developments in Statistics and Data Science.
Strong Theoretical Foundation
Students receive comprehensive training in:
- Probability Theory.
- Statistical Inference.
- Descriptive and Applied Statistics.
- Sampling Techniques.
- Regression Analysis.
- Design of Experiments.
- Time Series Analysis.
- Multivariate Analysis.
- Statistical Modelling.
- Research Methodology.
Practical and Computational Learning
The department emphasizes practical application through statistical computing and data analysis. Students gain exposure to appropriate statistical software, programming tools, data visualization techniques, and computational methods as part of their academic learning.
Research and Innovation
Students and faculty are encouraged to engage in research activities, academic projects, seminars, conferences, workshops, and interdisciplinary studies. The department promotes the application of statistical techniques to contemporary problems in science, business, economics, healthcare, social sciences, and other fields.
Department Highlights
- Autonomous academic curriculum with scope for periodic enrichment and innovation.
- Experienced and dedicated faculty committed to teaching and mentoring.
- Theory-integrated practical learning for better understanding and application.
- Statistical computing and data-analysis training.
- Student research projects and research-oriented academic activities.
- Workshops, seminars, conferences, and guest lectures.
- Interdisciplinary learning and collaborative research opportunities.
- Skill development programmes aligned with emerging career opportunities.
- Industry and academic interaction through invited experts and professional activities.
- Continuous mentoring and academic support for students.
- Encouragement for higher education and competitive examinations.
- Focus on analytical thinking, problem-solving, communication, and employability skills.
Student-Centric Learning
The department follows a student-centred approach that encourages active participation and experiential learning. Students are given opportunities to undertake projects, present research findings, participate in academic events, attend workshops, and apply statistical techniques to practical datasets.
The autonomous academic framework enables the department to introduce value-added courses, skill-based learning, project-based education, and emerging areas of Statistics according to the needs of students and the changing professional environment.
Career Opportunities
A degree in Statistics opens opportunities across several sectors, including:
- Data Analytics.
- Data Science.
- Banking and Finance.
- Insurance.
- Market Research.
- Healthcare.
- Government Sector.
- Business Intelligence.
- Research.
- Education.
- Information Technology.
- Scientific Research.
Students may also pursue higher studies such as M.Sc., M.Phil./Ph.D. and interdisciplinary programmes in Statistics, Data Science, Analytics, Economics, Computer Science, and related fields, subject to the eligibility requirements of the respective institutions.
Department at a Glance
Our Commitment
The Department of Statistics at Bharathiyar Arts and Science College for Women (Autonomous), Deviyakurichi continues to strengthen its academic and research profile by embracing emerging developments in Statistics, Data Analytics, Statistical Computing, and Data Science.
Through autonomous academic practices, innovative teaching, practical exposure, and research-oriented learning, the department is committed to nurturing capable, ethical, and responsible professionals who can contribute effectively to an increasingly data-driven society.
Shape Your Future with Statistics
Are you passionate about numbers, data, analytical thinking, and problem-solving? Build a strong foundation for a successful career in the data-driven world with the Department of Statistics.
As an Autonomous College, we provide a dynamic learning environment that combines academic excellence with practical training, statistical computing, research exposure, and skill development. Our programmes are designed to help students develop the knowledge and competencies required for higher education, research, and emerging careers in Statistics, Data Analytics, Data Science, Banking, Finance, Healthcare, Business Intelligence, and Research.
Why Choose Statistics at Our College?
- Autonomous and enriched curriculum.
- Experienced and dedicated faculty.
- Strong theoretical and practical foundation.
- Hands-on training in statistical computing and data analysis.
- Research and project-based learning.
- Workshops, seminars, guest lectures, and industry interaction.
- Opportunities for higher studies and career development.
- Student-focused mentoring and academic support.
Begin Your Journey Today
Take the first step towards a future powered by data and knowledge.
Vision & Mission
Department Vision
To become a centre of excellence in statistical education, research, and innovation by developing competent professionals with strong analytical and computational skills.
Department Mission
- To provide quality and contemporary education in Statistics.
- To utilize the academic autonomy of the institution to offer a flexible and industry-relevant curriculum.
- To develop students' analytical, computational, statistical, and research skills.
- To promote interdisciplinary research and the practical application of statistical methods.
- To provide hands-on training in statistical software, programming, and data analytics.
- To encourage innovation, independent learning, and lifelong professional development.
- To prepare students for higher education and diverse career opportunities.
Programmes Offered
Undergraduate Programme
The Department of Statistics offers an undergraduate programme designed to provide students with a comprehensive understanding of statistical concepts, analytical methods, computational techniques, and practical applications.
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B.Sc. Statistics
The programme develops a strong foundation in probability, statistical inference, data analysis, statistical modelling, sampling techniques, and research methodology.
B.Sc. Statistics
About the Programme
B.Sc. Statistics provides students with a comprehensive understanding of statistical theory, probability, statistical inference, data analysis, statistical modelling, and computational techniques. The programme combines theoretical learning with practical applications to prepare students for data-oriented professional opportunities.
Core Learning Areas
- Probability Theory.
- Statistical Inference.
- Descriptive and Applied Statistics.
- Sampling Techniques.
- Regression Analysis.
- Design of Experiments.
- Time Series Analysis.
- Multivariate Analysis.
- Statistical Modelling.
- Research Methodology.
- Statistical Computing.
- Data Analytics and Data Visualization.
Career Opportunities
- Data Analyst.
- Data Science Associate.
- Banking and Finance Executive.
- Insurance and Risk Analysis.
- Market Research Analyst.
- Healthcare Data Assistant.
- Business Intelligence Associate.
- Research Assistant.
- Government and Public Sector Opportunities.
- Higher Studies in Statistics and Data Science.
Learning Resources
Statistical and Computational Learning
The department emphasizes practical learning through statistical computing, data analysis, programming tools, and computational methods. Students are encouraged to apply theoretical knowledge to real-world datasets and develop analytical and problem-solving skills.
Academic Learning Resources
- Statistical textbooks and reference materials.
- Probability and statistical-method exercises.
- Statistical inference and modelling practice.
- Sampling and survey-based learning activities.
- Statistical software and data-analysis practice.
- Programming and computational learning.
- Research projects and statistical reporting.
- Workshops, seminars and guest lectures.
Research and Project-Based Learning
Students are encouraged to undertake academic projects, analyse practical datasets, prepare statistical reports, and present their findings. These activities strengthen research aptitude, communication skills, and evidence-based decision-making.
Staff Photos
| S.No. | Faculty Photo | Name | Designation |
|---|---|---|---|
| 1 |
|
C. Devaki | Head of the Department |
| 2 |
|
S. Prema | Faculty Member |
| 3 |
|
V. Manimegalai | Faculty Member |
| 4 |
|
A. Sharmila Banu | Faculty Member |
| 5 |
|
M. Sivaranjani | Faculty Member |
| 6 |
|
P. Paintamilselvi | Faculty Member |
| 7 |
|
M. Thangamani | Faculty Member |
| 8 |
|
S. Dhivyalakshmi | Faculty Member |
Syllabus
B.Sc. Statistics Syllabus
The syllabus provides the academic framework for the B.Sc. Statistics programme, covering theoretical subjects, practical components, computational learning, and research-oriented activities.
Refer to the approved syllabus documents for semester-wise subjects, course structure, credits, and academic requirements.
University Rank Holders
Academic Excellence
The Department of Statistics takes pride in recognizing students who have achieved outstanding academic performance and secured university ranks in the B.Sc. Statistics programme. Their accomplishments reflect dedication, perseverance, and academic excellence.
| S. No. | Student Name | Course | Academic Year | Rank |
|---|---|---|---|---|
| 1 | A. Pavithra | B.Sc. Statistics | 2013–2016 | I |
| 2 | M. Poornima | B.Sc. Statistics | 2013–2016 | III |
| 3 | R. Nivetha | B.Sc. Statistics | 2013–2016 | V |
| 4 | S. Vasanthapriya | B.Sc. Statistics | 2013–2016 | VI |
| 5 | A. Rajeshwari | B.Sc. Statistics | 2013–2016 | VII |
| 6 | S. Sangeetha | B.Sc. Statistics | 2013–2016 | IX |
| 7 | G. Vennila | B.Sc. Statistics | 2013–2016 | X |
| 8 | A. Sharmilabanu | B.Sc. Statistics | 2014–2017 | I |
| 9 | M. Priyanka | B.Sc. Statistics | 2014–2017 | IV |
| 10 | Snekha Ravisankar | B.Sc. Statistics | 2016–2019 | I |
| 11 | A. Kowsalya | B.Sc. Statistics | 2016–2019 | III |
| 12 | B. Indumathi | B.Sc. Statistics | 2016–2019 | V |
| 13 | M. Monalisa | B.Sc. Statistics | 2016–2019 | VII |
Centum Achievers
Student Academic Achievements
The Department of Statistics recognizes students who have secured centum marks in various subjects. These achievements demonstrate their academic commitment, subject knowledge, and consistent performance.
Academic Year 2016–2017 (Odd Semester)
| S. No. | Year | Student Name | Register Number | Paper Name |
|---|---|---|---|---|
| 1 | UG I | B. Indhumathi | 16UST10001 | Descriptive Statistics |
| 2 | UG I | A. Kowsaya | 16UST1003 | Descriptive Statistics |
| 3 | UG II | R. Sivanandhini | 15UST1005 | Distribution Theory |
| 4 | UG II | P. Thaslima Almariyam | 15UST1006 | Distribution Theory |
| 5 | UG III | M. Meenakshi | 14UST1001 | Regression Analysis |
| 6 | UG III | M. Priyanka | 14UST1002 | Regression Analysis |
| 7 | UG III | A. Sharmila Banu | 14UST1004 | Regression Analysis |
| 8 | UG III | A. Sharmila Banu | 14UST1004 | Non-Parametric Test |
Academic Year 2017–2018 (Odd Semester)
| S. No. | Year | Student Name | Register Number | Paper Name |
|---|---|---|---|---|
| 1 | UG I | M. Dhivya Bharathi | 17UST1002 | Descriptive Statistics |
| 2 | UG I | P. Nila | 17UST1006 | Descriptive Statistics |
| 3 | UG I | L. Pavithra | 17UST1007 | Descriptive Statistics |
| 4 | UG I | E. Thatchayani | 17UST1011 | Descriptive Statistics |
| 5 | UG III | S. Krishnaveni | 15UST1002 | Regression Analysis |
| 6 | UG III | R. Sivanandhini | 15UST1005 | Genentical Statistics |
| 7 | UG III | R. Sivanandhini | 15UST1005 | Non-Parametric Test |
Academic Year 2018–2019
| S. No. | Year | Student Name | Register Number | Paper Name |
|---|---|---|---|---|
| 1 | UG II | M. Dhivya Bharathi | 17UST1002 | Regression Analysis |
| 2 | UG II | M. Dhivya Bharathi | 17UST1002 | Matrix Algebra |
| 3 | UG II | P. Nila | 17UST1006 | Matrix Algebra |
| 4 | UG II | D. Prema | 17UST1008 | Matrix Algebra |
| 5 | UG II | E. Thatchayani | 17UST1011 | Matrix Algebra |
| 6 | UG II | S. Vijaya | 17UST1012 | Matrix Algebra |
| 7 | UG III | S. Kowsalya | 16UST1002 | Design of Experiments |
| 8 | UG III | Snekha Ravisankar | 16UST1006 | Testing of Hypothesis |
| 9 | UG I | N. Shobika | 18UST1007 | Probability Theory |
| 10 | UG I | E. Bavithra | 18UST1001 | Probability Theory |
| 11 | UG III | M. Monalisha | 16UST1004 | Statistical Forecasting |
Academic Year 2019–2020
| S. No. | Year | Student Name | Register Number | Paper Name |
|---|---|---|---|---|
| 1 | UG II | N. Shobika | 18UST1007 | Regression Analysis |
| 2 | UG III | M. Dhivya Bharathi | 17UST1002 | Testing of Hypothesis |
| 3 | UG III | G. Kanimozhi | 17UST1003 | Testing of Hypothesis |
| 4 | UG III | P. Nila | 17UST1006 | Non-Parametric Test |
Academic Year 2024–2025
| S. No. | Year | Student Name | Register Number | Paper Name |
|---|---|---|---|---|
| 1 | UG II | M. Madhumitha | C23UG103STA004 | Actuarial Statistics |
Academic Year 2025–2026 – Population Studies
| S. No. | Year | Student Name | Register Number | Paper Name |
|---|---|---|---|---|
| 1 | UG III | P. Agathiya | C23UG103STA001 | Population Studies |
| 2 | UG III | M. Madhumitha | C23UG103STA004 | Population Studies |
| 3 | UG III | V. Manjula | C23UG103STA005 | Population Studies |
| 4 | UG III | K. Sankari | C23UG103STA007 | Population Studies |
Academic Year 2025–2026 – Demography and Index Number
| S. No. | Year | Student Name | Register Number | Paper Name |
|---|---|---|---|---|
| 1 | UG III | M. Madhumitha | C23UG103STA004 | Demography |
| 2 | UG III | V. Manjula | C23UG103STA005 | Demography |
| 3 | UG III | K. Sankari | C23UG103STA007 | Demography |
| 4 | UG III | P. Agathiya | C23UG103STA001 | Index Number |
| 5 | UG III | S. Gomathi | C23UG103STA002 | Index Number |
| 6 | UG III | M. Madhumitha | C23UG103STA004 | Index Number |
| 7 | UG III | K. Sankari | C23UG103STA007 | Index Number |
| 8 | UG III | S. Shivani | C23UG103STA008 | Index Number |
| 9 | UG III | S. Vinitha | C23UG103STA010 | Index Number |
Department Annual Plan
Academic Planning
The department's academic planning focuses on strengthening statistical knowledge, computational skills, research aptitude, and student development. Activities include statistical software training, data-analysis exercises, seminars, workshops, project work, and academic interaction.
The autonomous curriculum provides opportunities to periodically enrich academic activities in response to emerging developments in Statistics, Data Analytics, and Data Science.
Department Achievements
Academic Achievements
The Department of Statistics encourages academic excellence, practical learning, analytical thinking, and research-oriented activities. Students are motivated to demonstrate their subject knowledge through university examinations, centum achievements, projects, workshops, and seminars.
- University rank holders in B.Sc. Statistics.
- Centum achievers in various Statistics papers.
- Student participation in academic programmes.
- Statistical computing and practical learning.
- Research-oriented projects and academic activities.
- Workshops and seminars by invited experts.
Workshops
Workshops and Skill Development
Workshops provide students with opportunities to gain practical knowledge, strengthen analytical skills, and understand emerging applications of statistical methods and computational tools.
Workshop List
| S. No. | Year | Date | Workshop Topic | Guest Name |
|---|---|---|---|---|
| 1 | 2026 | 07.08.2026 | Statistical Thinking Through Python | Dr. A. Pavithra, Assistant Professor, Department of Statistics (SF), PSG College of Arts and Science, Coimbatore – 614014. |
| 2 | 2025 | 14.03.2025 | Applications of Mathematics in Artificial Intelligence | Dr. K. Kalaiarasi, Assistant Professor, PG and Research Department of Mathematics, Cauvery College for Women (Autonomous), Trichy-18. |
Seminars
Academic Seminars
Academic seminars provide opportunities for students to learn about recent developments in statistical methodologies, research applications, data analysis, and emerging areas of statistical practice.
Seminar List
| S. No. | Year | Date | Seminar Topic | Guest Name |
|---|---|---|---|---|
| 1 | 2015 | 29.09.2015 | Recent Trends in Statistical Methodologies | Mr. S. Balasubramanimam, Assistant Professor, PG & Research Department of Statistics, EVR College, Trichy. |
Department Activities
Academic and Practical Activities
Department activities encourage students to apply statistical knowledge through practical exercises, data analysis, collaborative projects, research-oriented learning, and academic interaction.
- Statistical data collection and survey activities.
- Data organization, classification, and interpretation.
- Statistical computing and software-based exercises.
- Student research projects and presentations.
- Workshops on statistical applications and programming.
- Seminars and guest lectures by subject experts.
- Interdisciplinary learning and collaborative activities.
- Career guidance and higher education awareness.
Department Gallery
Student Photos
The department gallery showcases student participation, academic activities, workshops, seminars, classroom learning, and other department events.
Student Photograph
Student Photograph
Student Photograph
Department Activities Gallery
Add photographs of department workshops, seminars, student presentations, statistical activities, and academic events in this section.
Department Activities
Workshop
Seminar
Contact Details
Department of Statistics
For information about the B.Sc. Statistics programme, academic curriculum, syllabus, university rank achievements, workshops, seminars, and department activities, contact Bharathiyar Arts and Science College for Women (Autonomous), Deviyakurichi through its official communication channels.
Department: Statistics
Programme: B.Sc. Statistics
Institution: Bharathiyar Arts and Science College for Women (Autonomous)
Location: Deviyakurichi, Salem District.
