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Violin Plots: A Box Plot-Density Trace Synergism
Abstract
Many modifications build on Tukey's original box plot. A proposed further adaptation, the violin plot, pools the best statistical features of alternative graphical representations of batches of data. It adds the information available from local density estimates to the basic summary statistics inherent in box plots. This marriage of summary statistics and density shape into a single plot provides a useful tool for data analysis and exploration.
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“Popular visualizations of distributions are histograms, density plots, and violin plots (Hintze and Nelson [49] show multiple density plots side-by-side), but they seem to be hard for an uninitiated audience to grasp.”
From Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty (2021) · cites this paper as [49]
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Cites
Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,938
David, F. N., & Tukey, J. W. (1977) · Biometrics · doi:10.2307/2529486 · Cited by 12,707
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,514
Multivariate Density Estimation
Scott, D. W. (1992) · Wiley series in probability and statistics · doi:10.1002/9780470316849 · Cited by 3,786
Multivariate Density Estimation, Theory, Practice, and Visualbation
Ramsay, P. H. (1993) · Technometrics · doi:10.1080/00401706.1993.10485361 · Cited by 2,843
Mcgill, R., Tukey, J. W., & Larsen, W. A. (1978) · The American Statistician · doi:10.1080/00031305.1978.10479236 · Cited by 2,618
Graphical Methods for Data Analysis.
Healy, M. J. R., Chambers, J. M., Cleveland, W. S., Kleiner, B., & Tukey, P. A. (1984) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2981587 · Cited by 2,315
Graphical Methods for Data Analysis.
Fisher, N. I., Chambers, J. M., Cleveland, W. S., Kleiner, B., & Tukey, P. A. (1984) · Biometrics · doi:10.2307/2531418 · Cited by 1,982
Bulmer, M. (1978) · Sociology · doi:10.1177/003803857801200331 · Cited by 1,438
Applications, Basics and Computing of Exploratory Data Analysis.
Ross, G. J. S., Vellenian, P. F., & Hoaglin, D. C. (1983) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347963 · Cited by 844
Research works printed but not linked: 1
- Hintze J., 1997, User's Guide, NCSS 97, Statistical System for Windows
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Metadata
- Authors
- Hintze, J. L., & Nelson, R. D.
- Affiliations
- Brigham Young University (US)
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 1998-05
- Volume
- 52
- Issue
- 2
- Pages
- 181-184
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W2042204882
- Cited by
- 1,802
- References
- 17
- Citations by year
- 2026: 97 · 2025: 138 · 2024: 181 · 2023: 170 · 2022: 159 · 2021: 184 · 2020: 151 · 2019: 124 · 2018: 112 · 2017: 83 · 2016: 74 · 2015: 60 · 2014: 69 · 2013: 57 · 2012: 40
- FWCI
- 2.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The American Statistician (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
- Physical Sciences › Computer Science › Software › SAS software applications and methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- violin plots, box plots, density estimation, data visualization, summary statistics, exploratory data analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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What counts as a claim ›How we measure confidence ›How we check this ›
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