Here are 15 Common Data Fallacies to Avoid

This post is by Jeff Desjardins from Visual Capitalist

In today’s tech-driven economy, data is essential for gaining new insights, making decisions, and building products.

In fact, there is so much data out there, that the quantity of it is doubling every two years⁠—and by 2025, there will be 175,000 exabytes of data in existence.

This is an unprecedented figure, and it’s hard to put into perspective. To give you some sense, a single exabyte is equal to 1,000,000,000 GB of data, and five exabytes has been said to be roughly equal to “all of the words ever spoken by mankind”.

Common Fallacies With Data

As you can imagine, digging through all of this data can be quite the challenge.

Data comes in many different forms and not all of them are easy to analyze. As a result, it is tempting to take shortcuts with data, or to try and fit the incoming data we receive into our pre-conceived notions of how things ought to be.

Today’s infographic comes to us from Geckoboard and it shows the common mistakes that people make in analyzing data. We’ve reformatted their PDF to fit here.

15 Common Data Fallacies

Here are 15 Common Data Fallacies to Avoid

How do we avoid painting a bullseye around the arrow, so that we can interpret the meaning of data in a logical, consistent, and methodological way?

The key is to understand common mistakes that people make with data, and why these errors skew our interpretations.

Examples of Fallacies

Here are four examples of fallacies, and why each is considered a faux-pas by data (Read more...)