Informative Data Visualization with Raincloud Plots in JASP

Proper data visualization helps researchers draw correct conclusions from their data andfacilitates a more complete and transparent report of the results. In factorial designs,so-called raincloud plots have recently attracted attention as a particularly informativedata visualization technique; raincloud plots can simultaneously show summary statistics(i.e., a box plot), a density estimate (i.e., the cloud), and the individual data points (i.e.,the raindrops). Here we first present a ‘raincloud quartet’ that underscores the added valueof raincloud plots over the traditional presentation of means and confidence intervals. Theadded value of raincloud plots appears to be increasingly recognized: a focused literaturereview of plots in Psychonomic Bulletin & Review shows that 9% of plots in 2023 wereraincloud plots. Another 29% of plots (vs. 2% in 2013) contain individual data points (i.e.,raindrops), indicating a strong trend towards transparent and informative datavisualization. To further encourage this trend and make raincloud plotting easy andpractical for a broader group of researchers and students, we implemented a comprehensivesuite of raincloud plots in JASP, an open-source statistics program with an intuitivegraphical user interface. Examples from two factorial research designs illustrate how theJASP raincloud plots support a correct and comprehensive interpretation of the data.