We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    Flat editorial illustration: The article connects AI and marketing analytics with managerial judgment grounded in consumer behavi
    How an Online MBA in Marketing Connects AI and Data Analytics
    11 Min Read
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Data Visualization Doesn’t Need to be Biased
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > R Programming Language > Data Visualization Doesn’t Need to be Biased
R Programming Language

Data Visualization Doesn’t Need to be Biased

DavidMSmith
DavidMSmith
4 Min Read
Data Visualization Doesn't Need to be Biased
Photo by VentaRisk on Pixabay (https://pixabay.com/photos/arabic-script-writing-language-iraq-1174145/)
SHARE

At the FlowingData blog, data visualization commentator and Visualize This author Nathan Yau lists 5 misconceptions about visualization:

  • Software does everything (Nathan notes “Personally, I use a lot of R and have a lot of fun in Illustrator”, but uses a lot of other tools as well.)
  • Visualization is for making data flashy
  • The more information in a single graphic, the better
  • It has to be exact
  • Visualization is too biased to be useful

I agree completely with Nathan’s comments on the last point above:

There’s a certain amount of subjectivity that goes into any visualization as you choose what data to show and how to show it. By focusing on one part of the data, you might inadvertently obscure another. However, if you’re careful, get to know the data that you’re dealing with, and stay true to what’s there, then it should be easier to overcome bias.

After all, statistics is somewhat subjective, too. You choose what you analyze, what methods to use, and pick what to point out in reports.

News organizations, for example, have to do this all the time. They get a dataset, decide what story they want to tell (or find what story the data has to tell). Browse through graphics by The New York Times, and you can see how you can add a layer of information that objectively describes what the data is about.

This stands in contrast to the presentation I saw today at the Strata conference from Alex Lundry, Chart Wars: The Political Power of Data Visualization. (You can see a shorter version of his talk online). It was an entertaining talk, but his main point was to encourage data visualization partitioners to actively insert a point of view into the presentation of data. For example, he encourages more charts like the one on the right below, rather than the one on the left.

(Images from Nigel Holmes’ paper, Useful Junk? The Effects of Visual Embellishment on Comprehension and Memorability of Charts.)

More Read

Big Data Analytics a Key Enabler for Social CRM – Airlines Case Study
Big Data Analytics a Key Enabler for Social CRM – Airlines Case Study
R and Hadoop: Step-by-step Tutorials
Building Diversified Portfolios with R
Population health management with RevoScaleR
R Script Tracks Bookies’ Favorites for the Next Pope

Lundry’s take is that because the image on the right is more easily recalled by those who have seen it, it’s naturally better. I disagree. My objection to the chart on the right isn’t just that uses chartjunk, nor that the teeth are disporoportionately sized to the values, nor even that the X “axis” is slanted upwards to exaggerate the rise. My objection is the chart on the right is that it actively pushes an analysis upon the viewer. As Nathan notes, there’s always an element of bias in what data is selected to be presented, and the way it’s presented. But good charts merely present data, and leave the analysis (obvious though it may be) to the viewer. When a chart takes on the burden of analysis for the viewer, that’s when it strays from data visualization into propaganda.

FlowingData: 5 misconceptions about visualization 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article connects AI and marketing analytics with managerial judgment grounded in consumer behavi
How an Online MBA in Marketing Connects AI and Data Analytics
Analytics Artificial Intelligence Big Data Exclusive
Flat editorial illustration: The article connects commercial drone capture with integrated software workflows that organize and r
Drone Technology as a Business Investment: Calculating ROI, Costs, and Long-Term Value
Business Intelligence Marketing Software
Flat editorial illustration: The article connects weekly technician productivity and related shop metrics to timely scheduling an
Workforce Analytics for Auto Repair Shops: Reading Technician Productivity Weekly
Business Intelligence Exclusive
Flat editorial illustration: A business-editorial depiction of two account-growth routes: data-guided targeted advertising and cr
Targeted Ads and Cross-Promotion: Using Audience Segments and Platform Statistics to Grow
Exclusive Social Data

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Applications of R at Google
R Programming Language

Applications of R at Google

3 Min Read
How Google Uses R to Make Online Advertising More Effective
AnalyticsR Programming Language

How Google Uses R to Make Online Advertising More Effective

4 Min Read
Choosing Your First Programming Language
AnalyticsR Programming LanguageSoftware

Choosing Your First Programming Language

9 Min Read
Brian Ripley on The R Development Process
R Programming Language

Brian Ripley on The R Development Process

4 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?