Exploring Data Visually - Data Points: Visualization That Means Something - page 484

Each branch represents a user discussion about whether an article should be
deleted, and those that curl to the right are discussions that lean strongly for
deletion. A curl to the left is a discussion leaning toward keeping an article.
The more prominent the curl is, the stronger the agreement between users.
Although the visualization isn't traditional, you get still get something out of it.

That said, traditional visualization, such as bar graphs and line charts, can be
made easily and read quickly, which makes them great tools to explore data.

As your goals shift, so do your choices of visualization. If you were to design a
dashboard that provides the status of a system at a glance, you must visualize
the data in a way that is straightforward to digest. On the other hand, if the
goal is to encourage reflection or to evoke emotions, efficiency might not be
your main concern.

WHAT DO YOU SEE AND DOES IT MAKE SENSE?

After you visualize your data, there are certain things to look for, as shown
in Figure 4-4: increasing, decreasing, outliers, or some mix, and of course, be
sure you're not mixing up noise for patterns.

Also note how much of a change there is and how prominent the patterns are.
How does the difference compare to the randomness in the data? Observations
can stand out because of human or mechanical error, because of the uncer-
tainty of estimated values, or because there was a person or thing that stood
out from the rest. You should know which it is.

When you find something interesting, ask yourself: Does it make sense? Why
does it make sense? This is massively important.

The tendency is to automatically think of data as fact because numbers can't
possibly waver. But again, there's uncertainty attached to the data because
each data point is a snapshot of what happened during a moment in time.
You infer everything else.

Note: Inference and uncertainty: This is what
statistics is all about. If you can, take a statistics
course. Although you can learn a lot from visual
exploration alone, traditional statistics can help
you examine data in greater detail.

In the rest of this chapter, you look at specific data types
more closely. Keep the process in mind as you make your
way through.