Student Result Analysis

Project Overview

This project analyzes a dataset of student results to explore how different factors influence academic performance. The analysis includes:

• Distribution of gender and ethnic groups
• Impact of parental education on student scores
• Effect of parental marital status on academic performance
• Identification of outliers in scores

Data Source

The dataset used in this project can be found here.

Key Findings

• Gender Distribution: There are more female students than male students in the dataset.
• Parental Education: Higher parental education levels correlate with higher student scores.
• Parental Marital Status: Parental marital status has a negligible impact on student scores.
• Ethnic Group Distribution: Visual representation of the distribution of students among different ethnic groups.

Analysis and Visualization

The project includes various plots and visualizations to represent the data:

• Count plots for gender and ethnic group distribution
• Heatmaps to show the relationship between parental education and student scores
• Boxplots to identify outliers in Math, Reading, and Writing scores
• Pie charts for the distribution of ethnic groups

Technologies Used

• Python
• Pandas
• Matplotlib
• Seaborn

How to Run the Project

1. Clone the repository
2. Install the required libraries: numpy, pandas, matplotlib, seaborn
3. Run the Jupyter Notebook or Python script to see the analysis and visualizations

Conclusion

The analysis concludes that parental education has a direct impact on student academic performance, while parental marital status shows negligible impact. The visualizations help in identifying patterns and outliers in the data.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any questions or suggestions, please feel free to contact me at dornarajgyawali@gmail.com.