Data Analysis and Interpretation

Title: Data Analysis and Interpretation  

Date: 9th June 2023

Time: 10:00 AM – 5:00 PM 

Venue: Computer Lab 3, 4th Floor, BIIB, Sri Balaji University, Pune 

Venue: Hybrid (Online and Offline)

Organized by: Research & Development Cell, Sri Balaji University, Pune

Resource Person:

1. Dr. Shailesh Kasande, CEO and Group Director, Suryadatta Group of Institutes, Pune 

Introduction

Sri Balaji University, Pune (SBUP) organized a comprehensive Faculty Development Programme (FDP) on “Data Analysis and Interpretation” under the aegis of its Research & Development Cell. The objective was to enhance the statistical and analytical competence of faculty members through theoretical grounding and hands-on practice.

Objectives

• To acquaint participants with various data analysis techniques and tools.  
• To improve skills in interpreting and presenting data effectively. 
• To foster critical thinking and data-driven decision-making. 
• To enable the integration of analysis in academic disciplines. 
• To promote inter-departmental collaboration through shared learning.  

Session Design  

The day-long FDP was structured around lectures, demonstrations, interactive discussions, and practical data analysis exercises using SPSS. Opening remarks were delivered by Mr. Ramesh Jadhav, followed by an introduction to the program by Prof. Anil Keskar, Head of R&D Cell.

Key Areas Covered 

• Data Analysis Process: Types, collection, cleaning, and pre-processing.  
• Descriptive Statistics: Measures of central tendency and variability. 
• Inferential Statistics: Hypothesis testing, correlation, and regression.
• SPSS Tools: Hands-on activities with live datasets.
• Interpretation and Visualization: Meaningful data presentation strategies 

Participant Engagement  

Feedback and Outcomes

Participants appreciated the blend of theory and practice. Key takeaways included stronger data interpretation skills, real-time usage of tools like SPSS, and practical application of statistical methods in academic research. 

Conclusion

The FDP effectively bridged theoretical concepts with data-driven academic requirements, encouraging more confident and analytically sound research efforts among the faculty community.