Effectively designed data visualizations allow viewers to use their powerful visual systems to
understand patterns in data across science, education, health, and public policy. But …

Data can be visually represented using visual channels like position, length or luminance.
An existing ranking of these visual channels is based on how accurately participants could …

Idealized probability distributions, such as normal or other curves, lie at the root of
confirmatory statistical tests. But how well do people understand these idealized curves? In …

Univariate visualizations like histograms, rug plots, or box plots provide concise visual
summaries of distributions. However, each individual visualization may fail to robustly …

Visual validation of regression models in scatterplots is a common practice for assessing
model quality, yet its efficacy remains unquantified. We conducted two empirical …

How deep neural networks can aid visualization perception research is a wide-open
question. This paper provides insights from three perspectives—prediction, generalization …

People routinely rely on data to make decisions, but the process can be riddled with biases.
We show that patterns in data might be noticed first or more strongly, depending on how the …

Transparent research practices enable the research design, materials, analytic methods,
and data to be thoroughly evaluated and potentially reproduced. The HCI community has …

Immersive visualization in virtual reality (VR) allows us to exploit visual cues for perception
in 3D space, yet few existing studies have measured the effects of visual cues. Across a …

Empirical studies in visualisation often compare visual representations to identify the most
effective visualisation for a particular visual judgement or decision making task. However …