We live in a contemporary society surrounded by visuals, which, along with software options
and electronic distribution, has created an increased importance on effective scientific …

Heatmap is a widely used statistical visualization method on matrix‐like data to reveal
similar patterns shared by subsets of rows and columns. In the R programming language …

Graphical displays can reveal problems in a statistical model that might not be apparent from
purely numerical summaries. Such visualizations can also be helpful for the reader to …

Background People with pre-existing mental health conditions may be more susceptible to
stressors associated with COVID-19 relative to the general population; however, no studies …

The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny
focuses on the process of programming interactive web graphics for multidimensional data …

Algorithmic transparency entails exposing system properties to various stakeholders for
purposes that include understanding, improving, and contesting predictions. Until now, most …

We argue that statistical practice in the social and behavioural sciences benefits from
transparency, a fair acknowledgement of uncertainty and openness to alternative …

Spatial Data Science introduces fundamental aspects of spatial data that every data scientist
should know before they start working with spatial data. These aspects include how …

Seeing is believing, so goes the cliché. In our extremely online world, the particular nexus
between visual information and political belief has become one of the thorniest challenges …

The R package colorspace provides a flexible toolbox for selecting individual colors or color
palettes, manipulating these colors, and employing them in statistical graphics and data …