An exploratory research project analyzing how different physiological states (e.g., hunger, fatigue) influence human decision-making using statistical and psychological modeling techniques.
This study simulates and analyzes behavioral decisions under manipulated physiological states to identify patterns of risk-taking, impulsivity, and reward sensitivity. Data was collected from synthetic simulations and observational models.
- Psychological variable modeling (risk, reward, stress)
- CSV-based decision dataset analysis
- Statistical comparisons across physiological states
- Visual data plots of behavioral trends
| File / Folder | Description |
|---|---|
dataset.csv |
Experimental dataset |
analysis.py |
Data analysis and visualization |
model.py |
Behavioral model implementation |
requirements.txt |
Python package dependencies |
LICENSE |
MIT License |
Core Concepts Behavioral Economics
Cognitive Psychology
Decision-Making under Uncertainty ''' Experimental Simulations| pip install -r requirements.txt python analysis.py