About the Programme
Research is not only critical to the economic and social development of society; it is also critical to the mission of any University or academic institution. It is this research, which is the foundation for knowledge that makes possible much of the innovation and application that provides wider benefit. Research inculcates scientific and inductive thinking and it promotes the development of logical habits of thinking and organization. As Albert Einstein once remarked: "If we knew what it was we were doing, it would not be called research, would it”?. A need is always felt in quality-committed institutions to train the faculty and researcher in advanced research methodology in a manner that results in authentic and high-quality research, which has impact on the society, culture and future endeavours.
The present programme is designed to provide exposure to the participants on research problem formulation, application of appropriate research design and skills of data generation, data processing and statistical analysis at both, basic and advanced level. This CDP is intended to sharpen teaching and research skills of teachers, researchers and trainers, so that they are able to publish their work in SCOPUS/WOS/ICI/UGC indexed journals.
- Introduction to Research
- Research Design, Data & Sample Design
- Data Screening and Management
- Data Analysis
- Scientific Reporting
Who Should Attend
The programme is beneficial for faculty members and research scholars in academic institutions as well as executives working in research and consulting organization.
The resource persons will be from both industry and academia.
Time and Venue
One week programme will be conducted on-line via Google Meet during 25-30 July 2022.
After attending the programme, participants will acquire:
- Understanding need for research in Business & Management, Social Sciences etc.
- Familiarity with research process and methodology, review of literature, rationale and research objectives
- Understanding of hypotheses formulation and testing
- Knowledge about data collection and preparation.
- Presentation of data both in visual and inferential format.
- Scientific Reporting.