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Busting Fake News: Evaluating Online Information

Data Visualizations

Tips for Evaluating Data Visualizations

1. Identify the intended purpose of the visualization

Ask yourself: What is the purpose of the visualization? What is the claim?

2. Consider other factors that may shape the data and the visualization.

Ask yourself: What wasn't measured that could impact how the data is represented?

3. Consider the creator

Ask yourself: How may the creator be biased? Can you find more about who did the primary research? Do they have authority and experience in this area? How big was the sample size and how inclusive was it?

4. Reflect and Interpret

Ask yourself: what is the takeaway from the visualization? After evaluating the visualization, did your understanding of its claim change at all?

5. Infer further

What other information can you infer based on your interpretation of the visualization?

Evaluating Data and Statistics

It's just as important to evaluate the underlying data and statistics being represented in the visualization. Statistics can be easily manipulated or shared out of context in all types of media.

Examples of Misleading Data Visualizations

Truncated Axis

Take note of where the Y axis starts: 1.4 million instead of 0.

Corrected Axis

Changing the Y axis baseline to zero has a big impact on the visualization. In the previous version, there looked to be more significant differences in the number of visits, but with the adjusted Y axis, we can see that is not the case.

Confusing Pie Chart

Each slice of the pie is the same size but the labels showing different values add up to 193%. Each person was asked about their opinion of each candidate, so a pie chart is not the best graph for representing this data.

Better Bar Chart

Instead of a pie chart, this bar chart is a better was to represent the data of each person's response about each candidate. The baseline starts at zero and the different colors help distinguish the different candidates.