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Conceptual difficulties when interpreting histograms: A review

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Boels, Lonneke, Bakker, Arthur, Van Dooren, Wim, Drijvers, Paul·2019·Educational Research Review
DOI 10.1016/j.edurev.2019.100291
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Abstract

Histograms are widely used and appear easy to understand. Research nevertheless indicates that students, teachers and researchers often misinterpret these graphical representations. Hence, the research question addressed in this paper is: What are the conceptual difficulties that become manifest in the common misinterpretations people have when constructing or interpreting histograms? To identify these conceptual difficulties, we conducted a narrative systematic literature review and identified 86 publications reporting or containing misinterpretations. The misinterpretations were clustered and—through abduction—connected to difficulties with statistical concepts. The analysis revealed that most of these conceptual difficulties relate to two big ideas in statistics: data (e.g., number of variables and measurement level) and distribution (shape, centre and variability or spread). These big ideas are depicted differently in histograms compared to, for example, case-value plots. Our overview can help teachers and researchers to address common misinterpretations more generally instead of remediating them each individually.

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  • Distribution visualizations are often mistaken as bivariate case-value plots in which the lines or bars denote values instead of frequencies.

    “They are often mistaken as bivariate case-value plots in which the lines or bars denote values instead of frequencies [13].”

    From Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty (2021) · cites this paper as [13]

    Section 4.1.1 reports that histograms are widely misread as showing two variables and that their frequencies are often mistaken for measured values. Section 2.3.1 contrasts histograms with bivariate case-value plots. The review supports this confusion for histograms, but does not establish it for distribution visualizations generally or for plots with lines. (LLM, conf=0.84)

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Cited by

Sorted by citations

Authors
Boels, L., Bakker, A., Van Dooren, W., & Drijvers, P.
Affiliations
Utrecht University (NL)
Corresponding author
Boels, Lonneke
ORCID
Venue
Educational Research Review
Publisher
Elsevier BV
Published
2019-11
Volume
28
Pages
100291
ISSN
1747-938X (ISSN-L)
DOI
10.1016/j.edurev.2019.100291
OpenAlex
W2973465211
Cited by
47
References
4
Citations by year
2026: 5 · 2025: 4 · 2024: 13 · 2023: 8 · 2022: 13 · 2021: 2 · 2020: 2
FWCI
3.32
Type
journal article
Language
en
Open access
Licence
Locations
  • Educational Research Review (publishedVersion, cc-by)
  • Lirias (KU Leuven) (submittedVersion, other-oa)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
Funders
NWO (023.007.023)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
  • Social Sciences › Education › Educational Research and Methods
Keywords
histograms, conceptual difficulties, statistical literacy, data concepts, distribution concepts, levels of measurement, measurement scales, statistics education

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