How Do I Identify & Avoid Bias in Visualizing Data?

How Do I Identify & Avoid Bias in Visualizing Data?

Dr. Eleanor Small from Kenvue (formerly Johnson & Johnson Consumer Products) shares her experience identifying and avoiding bias in visual data like charts and graphs.

Beyond explaining the techniques people use to sway opinions, Dr. Small shows how it’s used to manipulate all of us every day with actual charts and graphs from the news and the internet.

She will also help you learn how to create good graphics that intentionally avoid data bias, including the best techniques to illustrate different types of data.

After this session, you’ll know what to look for when the news pulls up a graph to make a point or you see data presented on social media. Any time a graphic causes an emotional response, a healthy dose of skepticism is nearly always warranted.

Introduction & Agenda

1
Introduction
7:15

Dr. Eleanor Small kicks off the course with a look at a few different graphs that tell very different stories, then dives into her background in Consumer Health.

2
Agenda
1:26

From recognizing bias to preparing clear and robust presentations, Dr. Small previews what’s to come in the presentation.

Recognizing Bias

1
Five Primary Techniques Used to Mislead a Reader
2:11

Understand the techniques commonly used with graphs and infographics to mislead.

2
Omitting the Baseline
1:17

Armed with two examples of bar graphs zooming in on the Y axis, Dr. Small explains what omitting the baseline means.

3
Manipulating the Axis
3:49

See several examples of graphs where the axis has been manipulated.

4
Manipulating the Visual
5:53

Dr. Small discusses the various ways in which graphs can visually be manipulated.

5
Headlines & Annotations that Distract from Data
6:37

Learn how headlines or annotations can manipulate data so things are not really what they seem.

6
Choosing the Wrong Graph or Graphic
2:42

See two examples of when the wrong type of graph or graphic was chosen, and how confusing it is to look at the data!

7
Other Sources of Bias – Data Input or Design
3:37

This lesson shows an example of how data input can become biased, even if it’s accidental.

8
Other Sources of Bias – Hidden Bias
6:14

Dr. Small offers examples of hidden bias – an indirect one, and another due to a lack of data.

Choose the Right Format

1
Table or a Chart?
3:06

Do I use a table or a chart? Find out how to choose the right format for your data.

2
Types of Charts
2:30

From bar charts to bubble charts, Dr. Small explains how to know what the different types of charts are used for.

3
Axis Scale – Linear or Logarithmic
3:55

This lesson discusses when it makes sense to use a logarithmic scale instead of a linear scale.

4
Examples
5:29

Depending on how balanced your data is or how much data you have, you’ll want to choose a particular scale or a table vs. a chart. Here are some factors to consider, illustrated with examples.

5
Complicated Does Not Have to Mean Unclear
1:13

Even if you have a complicated point to get across with your data, you can still find a way to present it clearly! Dr. Small shows you an example of how.

Highlight the Critical Data

1
The Basics
3:35

Go over the basic elements of what you need to have when presenting your data.

2
Inset Plots
4:17

When should you use an inset plot? Dr. Small discusses in which situations it should be used.

3
Other Ways to Emphasize – Color
0:58

Understand how to use color to highlight a certain piece of data on a graph.

Robustness: Clear & Misprint-Proof

1
Robustness: Clear & Misprint-Proof
5:08

Learn some tips for “idiot-proofing” your data so you can get your point across, no matter what printing or technology issues you may encounter when presenting.

Recap & Closing

1
Recap & Closing
4:59

Dr. Small revisits the agenda items from the beginning of the presentation to recap the points we learned and answers a question about the viral illness graphs in the first lesson.

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Enrolled: 0 students
Duration: 1:16:16
Lectures: 20
Level: Intermediate

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