Abstract
Proper data visualization helps researchers draw correct conclusions from their data and facilitates a more complete and transparent report of the results. In factorial designs, so-called raincloud plots have recently attracted attention as a particularly informative data visualization technique; raincloud plots can simultaneously show summary statistics, a density estimate, and the individual data points.
The paper presents a raincloud quartet to show the added value of raincloud plots over more traditional summaries such as means and confidence intervals. It also reports a focused literature review suggesting that raincloud plots and plots with individual data points have become substantially more common in recent years.
To make this kind of visualization easier to use in practice, the paper accompanies the implementation of a comprehensive suite of raincloud plots in JASP, an open-source statistics program with a graphical interface. Examples from two factorial research designs show how the JASP raincloud plots support a more complete interpretation of the data.