JAMB 2024 Results Analysis

This project analyzes the JAMB 2024 exam results dataset (5000 rows) using Python.
The analysis explores relationships between study habits, attendance, teacher quality, and exam performance.
A Linear Regression model was built to predict JAMB scores.

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Key Findings

• Students with higher study hours, attendance, and completed assignments scored better.
• Model Performance:
  • Mean Squared Error (MSE): 1658.66
  • R² Score: 0.31 (the model explains ~31% of the variation in JAMB scores).

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Tools Used

• Python
• Pandas, NumPy
• Matplotlib, Seaborn
• Statsmodels
• Scikit-learn

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How to Use

1. Clone the repo:

   git clone https://github.com/Ezra-1233/Jamb-2024-Analysis.git