Missing the bar: How people misinterpret data in bar graphs

Date:
February 3, 2022
Source:
Wellesley College
Summary:
Thanks to their visual simplicity, bar graphs are popular tools for
representing data. But do we really understand how to read them? New
research has found that bar graphs are frequently misunderstood. The
study demonstrates that people who view exactly the same graph
often walk away with completely different understandings of the
facts it represents.



FULL STORY ========================================================================== Thanks to their visual simplicity, bar graphs are popular tools for representing data. But do we really understand how to read them? New
research from Wellesley College published in the Journal of Vision
has found that bar graphs are frequently misunderstood. The study
demonstrates that people who view exactly the same graph often walk away
with completely different understandings of the facts it represents.


==========================================================================
"Our work reveals that bar graphs are not the clear communication tools
many had supposed," said Sarah H. Kerns, a 2019 graduate of Wellesley,
research associate in its psychology department, and first author of the
paper, entitled "Two graphs walk into a bar: Readout-based measurement
reveals the Bar-Tip Limit error, a common, categorical misinterpretation
of mean bar graphs." "Bar graphs that depict mean values are ubiquitous
in politics, science, education, and government, and they are used
to convey data over a wide range of topics including climate change,
public health, and the economy," said co- author Jeremy Wilmer, associate professor of psychology at Wellesley. "A lack of clarity in domains such
as these could have far-reaching negative impacts on public discourse."
Kerns and Wilmer's revelation about bar graphs was made possible by a
powerful new measurement technique that they developed. This technique
relies upon having a person draw, on paper, their interpretation of the
graph. "Drawing tasks are particularly effective at capturing visuospatial thinking in a way that is concrete, expressive, and detailed," said
Kerns. "Drawings have long been used in psychology as a way to reveal
the contents of one's thoughts, but they have not previously been used to
study graph interpretation." The research team asked hundreds of people
to show where they believed the data underlying a bar graph would be by
drawing dots on the graphs themselves. A striking pattern emerged. About
one in five graph readers categorically misinterpreted bar graphs that
depicted averages. "These readers sketched all, or nearly all, of the
data points below the average," said Wilmer. "The average is the balanced center point of the data. It is impossible for the bulk of the data to be below-average. We call this mistake the bar-tip limit error, because the
viewer has misinterpreted the bar's tip as the outer limit of the data."
The error was equally prevalent across ages, genders, education levels,
and nationalities.

Given the severity of this error, how could decades of graph
interpretation research have missed it? "Previous research typically asked rather abstract, indirect questions: about predictions, probabilities,
and payoffs," said Kerns.

"It is difficult to read a person's thoughts from their answers to such questions. It is like looking through frosted glass -- one may gain a
vague sense of what is there, but it lacks definition. Our measurement
approach is more concrete, more direct, more detailed. The drawings
provide a clear window into the graph interpreter's thinking." "A major
lesson from this work is that simplification in graph design can yield
more confusion than clarification," said Wilmer. "The whole point of
replacing individual values with a summary statistic like an average,
is to simplify the visual display and make it easier to read. But this simplification misleads many viewers, and not only about the location of
the individual data points that have been removed -- it misleads them also about the average, which is the one thing the graph actually depicts."
The team suggests some changes in data visualization practices based on
their findings. First, they recommend that a bar be used only to convey
a single number, such as a count (150 hospital beds) or quantity ($5.75):
"In that case, no data is hidden," said Kerns. "In contrast, our research
shows that a bar used to depict the average of multiple numbers risks
severe confusion." Their second recommendation is to think twice before replacing concrete, detailed information (e.g., individual data points)
with visually simpler yet conceptually more abstract information (e.g.,
an average value). "Our work provides a case-in-point that abstraction
in data communication risks serious misunderstanding," said Wilmer.

The team's education-focused recommendations include the use of data
sketching tasks to teach data literacy. "Once a student's interpretation
is made explicit and visible on paper, it is easy to discuss and, if
necessary, correct," Wilmer said. They also suggest having students work
with real data. "Data is fundamentally concrete," Kerns said. "There is
value to reading about it in the abstract, but that will always be a bit
like reading a book to learn how to ride a bike. There is no substitute
for hands-on experience." Collection, visualization, and analysis of
data now form a centerpiece of all of Wilmer's courses. An enabling tool
in this effort is a free-access suite of data visualization web apps he
created at ShowMyData.org, which allow the user, in a matter of seconds,
to build and curate attractive, high-quality graphs with individual
datapoints. "Such graphs avoid the sorts of errors that our research
reveals," says Kerns. "And they are easily interpreted, even by young children," adds Wilmer, whose children, aged 11 and 7, are "two of my most astute (and ruthless) app development and data communication consultants."
In a political and scientific milieu where information spreads fast,
and where misunderstanding can have a profound impact on popular opinion
and public policy, clear data communication and robust data literacy are increasingly important. "From the grocery store to the doctors office
to the ballot box, data informs our decisions," Kerns said. "We hope
our work will help to enhance data comprehension and smooth the path
to informed decision-making by institutions and individuals alike."
special promotion Explore the latest scientific research on sleep and
dreams in this free online course from New Scientist -- Sign_up_now_>>> ========================================================================== Story Source: Materials provided by Wellesley_College. Note: Content
may be edited for style and length.


========================================================================== Journal Reference:
1. Sarah H. Kerns, Jeremy B. Wilmer. Two graphs walk into a bar:
Readout-
based measurement reveals the Bar-Tip Limit error, a common,
categorical misinterpretation of mean bar graphs. Journal of Vision,
2021; 21 (12): 17 DOI: 10.1167/jov.21.12.17 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220203102536.htm

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