Visualizing Anscombe’s Quartet in Style

Hello again. This week it is visualization week!

I enjoyed this assignment this week because it allowed me to explore the artistic side of data while comparing three powerful visualization techniques in R. The dataset I selected, Anscombe’s Quartet, was ideal for this exercise because it is simple, compact, and visually rich despite having no direct narrative. This dataset is special because all four quartets share the same statistical properties (mean, variance, correlation), yet their patterns become drastically different when plotted. This made it a perfect dataset to highlight the importance of visualization, and it gave me space to apply and compare all three methods: Base R, Lattice, and ggplot2.

The Base R visualizations were simple, intuitive, and easy to modify, making them great for quick exploratory analysis. With Lattice, I was blown away by the 3D feel of using cloud(), which allowed me to simulate a third dimension by mapping each dataset as a different group—even though the data is technically two-dimensional. This made me realize how flexible lattice can be when creating structured, multi-panel visualizations. Finally, ggplot2 was by far the most elegant, offering the most visually polished output with clean themes and layered customization. Using these techniques, I now feel more confident in showcasing data effectively—even when the message isn’t in the numbers alone but in the patterns the visuals reveal.

Here are the three visualizations requested by the assignments.

Please 📂Check out my complete code on GitHub!

Base R – Scatterplots with regression lines (no extra packages were loaded)