The Box-Percentile Plot

By W. Esty, Jeff Banfield. 2003

93 citations recorded by the source corpus.

A variant of the boxplot is proposed in which the sides contain the information of a percentile plot (which is equivalent to the empirical cumulative distribution function). Unlike boxplots, there is no question about how long to draw the whiskers, nor is there loss of information due to grouping. Side-by-side comparisons of distributions are especially effective. In spite of including more detail, the impact on statistically-untrained readers remains similar to that of traditional boxplots.

Subfields: Food Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c1ebaeb667ed0ec7801c2c9dcbf6c26082d3e54c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Food Science

1. Lisa Stryjewski
2. Hadley Wickham

In Statistics and Probability

1. Heike Hofmann
2. Lisa Stryjewski
3. Hadley Wickham
4. Michael C. Sachs
5. David J. Kahle

Citations in the corpus

• Letter-Value Plots: Boxplots for Large Data (2017, background): “The overview article by Wickham and Stryjewski (2012) discusses these alternatives, in particular vase (Benjamini 1988), violin (Hintze and Nelson 1998), bean (Kampstra 2008), box-percentile (Esty and Banfield 2003), and high-density region (Hyndman 1996) plots.”
• Displaying Uncertainty With Shading (2008, unknown): “This principle was extended by Esty and Banfield (2003) to illustrate the entire empirical distribution of data as a box-percentile plot.”
• 40 years of boxplots (2010, background): “4 Box-percentile plots The box-percentile plot 6, introduced by Esty and Banfield [5], differs from other density boxplots in that it does not use kernel density estimation to plot the density curve.”