7-Day FDP on “Data Analysis Using SPSS”
In Collaboration with: D.K.T.E. Society’s Textile & Engineering Institute, Ichalkaranji, Maharashtra
Date: August 11 – August 18, 2025
Time: 07:00 PM – 08:00 PM IST
Total Participants: 95
Mode: Online via Zoom
Topic: Data Analysis Using SPSS
Scrollwell, in collaboration with D.K.T.E. Society’s Textile & Engineering Institute, Ichalkaranji, Maharashtra, organized a 7-Day Online Faculty Development Program (FDP) on Data Analysis Using SPSS from August 11 to 18, 2025. The FDP aimed to bridge the gap in research data handling and strengthen participants’ ability to apply statistical tools effectively for academic, research, and professional purposes.
The program witnessed enthusiastic participation, with 95 participants including faculty members, research scholars, academicians, and professionals from various institutions.
Event Highlights
Day 1 – August 11, 2025
Topic: Introduction to SPSS, Data Coding, and Tabulation
Participants were introduced to the SPSS environment, its interface, and core functionalities. The session included data entry methods, coding variables, data cleaning, and managing missing values. The basics of tabulation and data summarization were also practiced through hands-on exercises.
Day 2 – August 12, 2025
Topic: Descriptive Statistics
This session covered essential descriptive statistics including mean, median, mode, range, variance, and standard deviation. Participants also learned to perform normality checks and distribution analysis.
Day 3 – August 13, 2025
Topic: Correlation Analysis
The focus was on understanding correlation techniques such as Pearson, Spearman, and Kendall correlations. Real-time datasets were used to demonstrate interpretation and application in research contexts.
Day 4 – August 14, 2025
Topic: Regression Analysis and Interpretation
Participants explored regression models, including simple and multiple linear regression. Emphasis was placed on model building, validation, and interpretation of outputs. Case-based exercises enabled participants to apply regression techniques to practical problems.
Day 5 – August 15, 2025
Holiday – Independence Day
No session was conducted on this day. The holiday provided participants a valuable break to revise previous sessions and prepare for upcoming advanced topics.
Day 6 – August 16, 2025
Topic: Factor Analysis in SPSS
This session introduced Factor Analysis and Principal Component Analysis (PCA). Participants explored factor extraction methods, scree plots, and interpretation of factor loadings. The session highlighted the application of factor analysis in social sciences and market research.
Day 7 – August 17, 2025
Topic: Cluster Analysis
Participants learned clustering techniques including hierarchical and K-means clustering. The session demonstrated methods for determining optimal cluster numbers and their application in market segmentation and research. Case studies enhanced understanding of clustering applications.
Day 8 – August 18, 2025
Topic: Project, Evaluation, and Interpretation
On the final day, participants worked on mini-projects where they applied SPSS tools to analyze real-world datasets. This served as an evaluation of their learning and helped them gain confidence in independently performing statistical analysis.
Outcomes of the FDP
- Strengthened participants’ ability to analyze data using SPSS with confidence.
- Improved understanding of statistical methods including descriptive analysis, correlation, regression, factor, and cluster analysis.
- Enhanced research and analytical skills of faculty members, scholars, and professionals.
- Participants developed hands-on experience through guided lab sessions.
- The program created a collaborative environment for academic and professional growth.
Acknowledgment
We extend our heartfelt gratitude to D.K.T.E. Society’s Textile & Engineering Institute, Ichalkaranji, Maharashtra, for collaborating and supporting this FDP. Special thanks to Dr. Prabal Chakraborty, resource person for the sessions, for his expert guidance and engaging delivery throughout the program. We also thank all participants for their active involvement and commitment to learning.
