Visually-Weighted Regression

Uncertainty in regression can be efficiently and effectively communicated using the visual properties of statistical objects in a regression display. Altering the “visual weight” of lines and shapes to depict the quality of information represented clearly communicates statistical confidence even when readers are unfamiliar with the formal and abstract definitions of statistical uncertainty. Here we present examples where the color-saturation and contrast of regression lines and confidence intervals are parametrized by local measures of an estimate’s variance. The results are simple, visually intuitive and graphically compact displays of statistical uncertainty. This approach is generalizable to almost all forms of regression. ∗Email: [email protected]. The programs described in this paper are available at the author’s website: www.solomonhsiang.com/computing/data-visualization. I thank Marshal Burke, Andrew Gelman, and Reed Walker for helpful suggestions.