Visually-Weighted Regression

10 Pages Posted: 17 May 2013

See all articles by Solomon Hsiang

Solomon Hsiang

University of California, Berkeley; National Bureau of Economic Research

Date Written: May 2013

Abstract

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, 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.

Keywords: regression, data visualization, statistics

JEL Classification: C10, C88

Suggested Citation

Hsiang, Solomon, Visually-Weighted Regression (May 2013). Available at SSRN: https://ssrn.com/abstract=2265501 or http://dx.doi.org/10.2139/ssrn.2265501

Solomon Hsiang (Contact Author)

University of California, Berkeley ( email )

2607 Hearst Avenue
Berkeley, CA 94720-7320
United States

HOME PAGE: http://gspp.berkeley.edu/directories/faculty/solomon-hsiang

National Bureau of Economic Research ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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