5 Common Data

Visualization Mistakes(and how to avoid making them)

Wrong Chart Type

Dataviz Mistake #1

This chart

falsely implies

that 1/3 of all

preterm births

are to Non-

Hispanic Black

mothers.

A bar chart

more

accurately

portrays the

relationship of

preterm births

to race.

Too Complicated

Dataviz Mistake #2

This chart

displays

information

culled from a

141 page report.

Its complexity

hampers

communication.

The point of the

infographic is that

BrandZ can provide

insight on the world

marketplace. This

small portion of the

visualization

accomplishes the

same goal.

Skewed Correlation

Dataviz Mistake #3

The circles’ sizes

exaggerate the

number of deaths

per disease in

relation to

money raised.

While not as

dramatic, this

visualization

correctly

correlates money

donated with

deaths per

disease.

Omitting Key Information

Dataviz Mistake #4

Without

context it’s

impossible to

determine the

significance of

the U.S.’s

increase in oil

production.

russiaSaudiiraqChina United

arab

brazil

Providing data

enables viewers

to see the extent

of the U.S.’s

increase in oil

production

compared to

other countries.

Bucking Conventions

Dataviz Mistake #5

The inversion

of this chart’s

y axis makes

it seem that

gun deaths

decreased

after 2005.

Flipping the

chart makes it

much more

clear that gun

deaths actually

increased after

2005.

Five dataviz mistakes to avoid:

Wrong Chart

Type

Too

Complicated

Skewed

Correlation

Omitting Key

Information

Bucking

Conventions

Summary

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