Gautam Buddha University promotes AI, advanced statistical tools in research

The sixth day, Tuesday, featured sessions covering generative AI, descriptive statistics, and inferential methods, helping researchers enhance their statistical and analytical skills

NOIDA: A 10-day Research Methodology Course (RMC) at Gautam Buddha University (GBU) is promoting academic excellence and enhancing research capabilities, the university administration said on Tuesday.

Designed to equip researchers with practical skills and advanced knowledge, the programme focuses on blending modern technology with traditional research tools. (HT Photo)

Designed to equip researchers with practical skills and advanced knowledge, the programme focuses on blending modern technology with traditional research tools. Through expert-led sessions, the course fosters a collaborative and innovative research ecosystem, addressing both theoretical and applied research needs.

The course aims to provide participants with practical experience in applying advanced research methodologies, said Dr. Arvind Kumar Singh, assistant professor and director of International Affairs at the university.

The sixth day, Tuesday, featured sessions covering generative AI, descriptive statistics, and inferential methods, helping researchers enhance their statistical and analytical skills.

The day began with a session led by Prof. SM Khan on “Development and Standardisation of Tests – Generative AI.”

Prof. Khan highlighted how generative AI is transforming academic and research frameworks by enabling assessments to become more adaptive and personalised. He explained how AI-based tools can improve test design and standardisation, offering researchers insights into AI’s practical applications in modern research.

During the second session, Prof. Khan focused on descriptive statistics, particularly testing for normality.

He provided participants with foundational knowledge on analysing data distribution and assessing normality.

The session emphasised on the importance of conducting such tests to ensure accurate interpretation of research outcomes.

The day concluded with a session by Prof. Gaurav Garg on inferential statistics, specifically non-parametric tests.

Prof. Garg discussed techniques for handling non-normally distributed data, equipping participants with essential tools for robust data analysis. He explained the significance of non-parametric methods in modern research, helping participants gain confidence in analysing complex datasets.