Adding uncertainty representation in a data visualisation can help in decision-making. There is an existing wealth of software designed to visualise uncertainty as a distribution or probability. These visualisations are excellent for helping understand the uncertainty in our data, but they may not be effective at incorporating uncertainty to prevent false conclusions. Successfully preventing false conclusions requires us to communicate the estimate and its error as a single “validity of signal” variable, and doing so proves to be difficult with current methods. In this talk, we introduce ggdibbler, a ggplot extension that makes it easier to visualise uncertainty in plots for the purposes of preventing these “false signals”. We illustrate how ggdibbler can be seamlessly integrated into existing visualisation workflows and highlight the effect of these changes by showing the alternative visualisations ggdibbler produces for a choropleth map.