Student Performance Analysis

Problem Statement

Analyze student academic performance and identify demographic and educational factors that influence math, reading, and writing scores.

Dataset

Students Performance in Exams dataset from Kaggle.

Features:

• gender
• race/ethnicity
• parental level of education
• lunch
• test preparation course
• math score
• reading score
• writing score

Tools Used

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn

Project Structure

Student-Performance-Analysis/ ├── Data/ ├── Notebooks/ ├── Images/ ├── Report.pdf ├── README.md

Steps Performed

1. Loaded and inspected the dataset
2. Handled missing values and duplicates
3. Encoded categorical variables (gender, parental education)
4. Performed exploratory data analysis (EDA)
5. Created visualizations
6. Extracted actionable insights

Key Insights

• Math, reading, and writing scores are strongly correlated
• Parental education has a limited but positive impact on scores
• Gender-based performance differences vary by subject
• Reading and writing scores show higher alignment than math

Visualizations

Conclusion

Student performance is influenced more by subject relationships and preparation factors than by demographic attributes alone. Educational interventions should focus on balanced skill development rather than isolated subjects.