Analysis of holopelagic Sargassum spp. biomass composition using advanced statistical techniques.
This project explores the biomass composition of holopelagic Sargassum spp. — seaweed drifting in open ocean systems — with the goal of understanding how factors like processing method, seasonality and volcanic ash influence biomass structure and element content.
Key statistical techniques applied:
- Principal Component Analysis (PCA) – to reduce dimensionality and identify major variation drivers
- Linear Discriminant Analysis (LDA) – to distinguish groups based on processing/seasonal categories
- Random Forest – to model predictive relationships between biomass features and external factors
STATS-Coursework/
│
├── biocomposition_analysis.R ← Main analysis script
├── dataset1.csv ← Raw biomass data (processing method)
├── dataset2.csv ← Seasonal/ash-impact data
└── final_coursework.Rproj ← RStudio project file