From February 26 to April 15, 2024, the Department of Health and Hospital Administration at the College of Administration and Economics successfully conducted a training course aimed at “Mastering Data Analysis with SPSS Software.” Led by Assistant Professor Dr. Sohail Imrankhan and Assistant Lecturer Ronyaz Hayass, the course provided an intensive eight-week program covering various aspects of SPSS software.
Each week of the course was meticulously structured to cover specific topics, beginning with the foundation of SPSS and gradually progressing to more advanced analyses:
- Week 1: Foundation of SPSS
- Introduction to SPSS software and basic functions.
- Understanding the statistical concepts underlying data analysis.
- Week 2: SPSS Interface
- Navigating the SPSS interface efficiently.
- Customizing preferences for optimal usability.
- Week 3: Data Entry in SPSS
- Techniques for entering data accurately and efficiently.
- Handling missing data and data cleaning procedures.
- Week 4: Cronbach’s Alpha
- Understanding reliability analysis using Cronbach’s alpha.
- Interpreting and reporting results from reliability tests.
- Week 5: Presentation of Data
- Techniques for visually presenting data using charts and graphs.
- Best practices for creating informative and visually appealing data presentations.
- Week 6: Description of Variables
- Exploring descriptive statistics for summarizing and describing data.
- Interpreting measures of central tendency and dispersion.
- Week 7: Correlation Analysis
- Understanding correlation analysis and its applications.
- Interpreting correlation coefficients and assessing the strength of relationships.
- Week 8: Regression Analysis
- Introduction to regression analysis and its role in predictive modeling.
- Interpreting regression coefficients and assessing model fit.
Throughout the course, Dr. Sohail Imrankhan and Assistant Lecturer Ronyaz Hayass collaborated closely to provide comprehensive instruction and guidance to participants. The training course not only equipped attendees with practical skills in data analysis but also fostered a collaborative learning environment where participants could exchange ideas and insights.
On April 15, 2024, at the end of the training course, certificates were distributed to both the trainers and participants, acknowledging their successful completion of the program.
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