---
dataset_info:
  features:
  - name: phone_hours
    dtype: float64
  - name: computer_hours
    dtype: float64
  - name: device_count
    dtype: int64
  - name: sleep_quality
    dtype: string
  - name: use_before_bed
    dtype: int64
  - name: sleep_time
    dtype: int64
  - name: sleep_hours
    dtype: float64
  splits:
  - name: original
    num_bytes: 1697
    num_examples: 30
  - name: augmented
    num_bytes: 16964
    num_examples: 300
  download_size: 8644
  dataset_size: 18661
configs:
- config_name: default
  data_files:
  - split: original
    path: data/original-*
  - split: augmented
    path: data/augmented-*
---

## Dataset Summary
This dataset records **daily electronic device usage** and **sleep patterns** of students.  
It is designed for exploring the relationship between screen time, device behavior, and **average sleep duration**.

- **Original size:** 30 samples  
- **Augmented size:** 300 samples  
- **Task type:** Regression (predicting daily sleep hours)  
- **Goal:** Predict `sleep_hours` from usage and sleep-related features  


## Data Splits
- No fixed train/test split is provided.  
- Users can apply their own strategy (e.g., 80/20 split).  


## Intended Uses
- **Regression Task:** Predict `sleep_hours` from device usage.  
- **Correlation Analysis:** Study relationships between screen time and sleep quality.  
- **Education:** Demonstrates dataset augmentation (30 → 300 samples).