Skills and Insights Gained

This project was a collaborative effort between my team and me for the STAT467 Multivariate Analysis course. Our objective was to explore various multivariate statistical techniques using R to analyze wine quality data. The key research questions focused on understanding the impact of wine color and chemical properties on quality and alcohol content.

Our project included:
- Exploratory Data Analysis (EDA): Visualizing and summarizing the dataset,
- Principal Component Analysis (PCA) & Regression: Dimensionality reduction and modeling,
- MANOVA and Hypothesis Testing: Investigating mean differences across wine colors,
- Factor Analysis & Rotation: Identifying latent variables in the dataset,
- Clustering & Classification: Grouping wines based on key characteristics,
- Canonical Correlation Analysis (CCA): Exploring relationships between chemical and sensory properties.

This project strengthened my statistical modeling skills in R and provided hands-on experience with real-world multivariate techniques. The full analysis and code are available on GitHub.