In 1973, statistician Francis Anscombe challenged the commonly held belief that “numerical calculations are exact, but graphs are rough” (Anscombe, 1973). His strategy was to manually construct four small datasets—now known as Anscombe’s Quartet—that have different distributions but nearly identical descriptive statistics. It’s perhaps the best argument for visualizing data.
In this notebook we replicate his paper by using Plotnine to visualize those datasets and Polars to verify their descriptive statistics. More specifically, we:
A mentorship experience during undergrad opens up opportunities for learning about text analysis, as well as meta-skills like debugging and reproducibility.
We started the RStudio project because we were excited and inspired by R. The creators of R provided a flexible and powerful foundation for statistical computing; then made it free and open so that it could be improved collaboratively and its benefits could be shared by the widest possible audience.
It’s better for everyone if the tools used for research and science are free and open. Reproducibility, widespread sharing of knowledge and techniques, and the leveling of the playing field by eliminating cost barriers are but a few of the shared benefits of free software in science.
