https://github.com/nadahamdy217/university-subjects-opinion-survey-analysis-project

https://github.com/nadahamdy217/university-subjects-opinion-survey-analysis-project

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• Host: GitHub
• URL: https://github.com/nadahamdy217/university-subjects-opinion-survey-analysis-project
• Owner: nadahamdy217
• Created: 2024-08-11T10:11:28.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-11T20:00:22.000Z (5 months ago)
• Last Synced: 2024-11-07T15:35:10.334Z (about 2 months ago)
• Language: Jupyter Notebook
• Size: 2.92 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
📊 Survey Data Analysis


This repository contains a Jupyter notebook focused on the analysis of survey data, exploring both descriptive and inferential statistics to derive meaningful insights.


🔍 Project Overview


The analysis covers various aspects of survey data from students, including their academic performance, perception of course materials, and learning environment. The main objectives of this project are to understand the relationship between different variables and to identify areas of improvement in the educational process.


📂 Key Sections




  


Descriptive Analysis

    


      


Frequency Analysis: Examines the distribution of student gender, CGPA, material sufficiency, and the adequacy of practical examples.

      


Mode Analysis: Evaluates the relevance of assignments, the impact of the working environment on performance, and classroom conditions.

      


Percentage Analysis: Investigates the prevalence of soft skills among students and the perceived relevance of courses to job readiness.

      


Cross Tabulation: Analyzes relationships between variables, such as the impact of gender on CGPA and the correlation between doctor and assistant cooperation.

    

  

  

  


Inferential Statistics

    


      


Chi-Square Test: Tests the significance of relationships between categorical variables, including gender and GPA, and the effectiveness of interactive teaching techniques.

    

  


  


Correlation Analysis

    


      
Measures the correlation between categorical variables to understand their relationships.

    

  



📈 Results & Insights




  


Gender and Academic Performance: The analysis indicates that gender may influence CGPA, with females generally having higher GPAs.

  


Interactive Teaching: There is evidence that interactive teaching techniques positively impact student outcomes.

  


Material Sufficiency: Students perceive that there are not enough practical examples, and course materials could be clearer.



⚙️ How to Use


To run the analysis, ensure you have the required dependencies installed. You can execute the notebook in a Jupyter environment to see the detailed analysis and results.


🤝 Contributing


Contributions are welcome! Please fork this repository and submit a pull request with your improvements.