Snail Length Prediction
This project explores relationships between snail shell lengths and various morphometric predictors using statistical learning methods. We performed exploratory analysis, evaluated transformations of the response variable, and built both simple and multiple linear regression models. Advanced techniques, including interaction exploration and random forests, were applied to improve prediction accuracy. The project combines rigorous data analysis with clear visualizations to understand key factors influencing snail growth patterns.


