Graphic Stories

Date01 March 2017
Published date01 March 2017
AuthorTim Chartier
© 2017 Wiley Periodicals, Inc.
Published online in Wiley Online Library (
DOI 10.1002/jcaf.22252
Graphic Stories
Tim Chartier
The amount of data avail-
able for analysis is a
modern and dynamic
phenomenon. Analyzing data
to encourage action is not new.
The massive data sets of today
make initial analysis manda-
tory in order to ensure its qual-
ity and reliability. This, too, is
not new. In 1977, famed statis-
tician John Tukey published a
highly influential book entitled
Exploratory Data Analysis in
which he recommended start-
ing data analysis with graphical
tools, in particular constructing
and viewing a box and whisker
plot to see the maximum, mini-
mum, median, and first and
third quartiles. Often, graphics
offer an analyst valuable insight
and intuition that directly lead
to insightful analytics. Well-
crafted visualizations can also
tell a story.
As an example, we turn
to the Crimean War, which
occurred from 1853 to 1856,
and led to over half a million
casualties on all sides. The
mother of modern nursing,
Florence Nightingale, volun-
teered during this war. She
compiled data on the deaths of
soldiers, as she was especially
concerned with the unsanitary
condition of the hospitals and
its impact on many lives.
To present her work, she
developed a circular histogram
that she called a “Coxcomb”
as seen at the top of the next
page. Nightingale presented
her graph to Queen Victoria
and to members of Parlia-
ment and civil servants. The
graphic clearly unfolded the
story of soldiers’ deaths. The
lightest gray represents deaths
by wounds. The next lightest
shade of gray corresponds to
deaths by disease, and black
depicts deaths by other causes.
The graph clearly demonstrates
that far more soldiers died from
preventable diseases than from
their battle wounds. The visual-
ization led to improved sanitary
conditions in the military hos-
pitals, which resulted in greatly
reduced the numbers of deaths
in the remainder of the war.
Modern graphics are often
created to be informative and
to allow for quick understand-
ing of the underlying data.
When you use graphical tools
to communicate or analyze
data, you rely on our brain’s
way of processing graphi-
cal information. The “Power
of Infographics” by Mark
Smiciklas states that 50% of
the brain is dedicated directly
or indirectly to visual functions.
Further, modern tools allow a
user to explore data through
graphical tools. For example,
my sports analytics group that
supplies data for the men’s
basketball team had a spring
meeting with the coaches to
review the season and plan for
the next year.
Like Nightingale, we pre-
pared a graphical tool for
the presentation. One of my
student analysts presented
an interactive graphic and
quickly outlined how to read
the visualization. Moments
later, an assistant coach asked
the question, “Can we explore
the middle region of the graph
a bit more? That’s interesting
that those two players’ interac-
tions are so different than the
rest.” The student moved to
another visualization tool and
rendered an image utilizing
data from the earlier graphic.
We all sat silently and then the
coaches said, “That would be
why we made a rule during the
season that such a shot could
not be taken.” The graphic
made it very clear that the team
missed shots of a certain type.
The team, in fact, missed them
every time. Note, the coaches
didn’t receive new insight. But
the analysis strongly affirmed a
decision they made during half-
time in a game and then kept in

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