This repository contains two data analysis projects conducted in R, demonstrating exploratory analysis, statistical modeling, and predictive techniques.
- Objective: Identify trends in listener preferences using Spotify streaming data.
- Techniques: Unsupervised learning – Cluster Analysis, Principal Component Analysis (PCA)
- Outcome: Grouped songs and listeners into meaningful clusters, uncovering patterns in music consumption.
- Objective: Predict whether a website visitor will make a purchase based on browsing behavior.
- Techniques: Supervised learning – classification models
- Outcome: Built predictive models that estimate the probability of purchase, providing insights into consumer habits.
- R
- RStudio
- Statistical learning packages (e.g., caret, stats)
- Data visualization with ggplot2 and base R
These projects demonstrate practical application of statistical and machine learning techniques in R for both exploratory and predictive data analysis.