Predict Student Performance

Description

This dataset is a synthetic representation of student performance, designed to mimic real-world scenarios by considering key factors such as study habits, sleep patterns, socioeconomic background, and class attendance. Each row represents a hypothetical student, and the dataset includes both input features and the calculated target variable (grades).

The dataset can be used for predictive modeling, exploratory data analysis, or even as a beginner-friendly introduction to machine learning workflows.

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Key Features

1. Study Hours

   • Description: Average daily hours spent studying.

2. Sleep Hours

   • Description: Average daily hours spent sleeping.

3. Socioeconomic Score

   • Description: A normalized score (0-1) indicating the student's socioeconomic background.

4. Attendance (%)

   • Description: The percentage of classes attended by the student.

5. Grades (TARGET)

   • Description: The final performance score of the student, derived from a combination of study hours, sleep hours, socioeconomic score, and attendance.

Usage Notes

• This dataset is synthetic and does not represent real students. It was created for educational and demonstration purposes.
• While the dataset strives for realism, it includes controlled randomness and noise to simulate real-world data variability.

Acknowledgments

This dataset is a beginner-friendly introduction to synthetic dataset creation, aiming to help the community experiment with realistic yet controlled data. Happy exploring! 🚀