Project case study
Iris Dataset Statistical Analysis
A comprehensive R data science project using statistical analysis, publication-ready visualisation and classification to understand the Iris flower dataset.
What was the project?
The project analysed the classic Iris dataset to demonstrate a complete statistical workflow: explore the data, test relationships, visualise patterns and assess classification performance.
Problem and approach
The analytical objective was to identify the measurements that best distinguish flower species. The workflow combined descriptive statistics, hypothesis tests, ggplot2 visualisation, dplyr transformations and machine learning algorithms in an RMarkdown report.
Delivered outcomes
- Applied statistical tests and classification models.
- Identified features separating species in exploratory analysis.
- Created publication-ready visualisations.
- Generated a reproducible RMarkdown report.
Skills demonstrated
Statistical reasoning, exploratory data analysis, R programming, data visualisation, classification and scientific communication.