Good Graphs

What makes a good graph?

It’s easy to spot a bad graph.

I’m sure everyone has seen graphs before that only made the data more confusing. A quick search will turn up many. Sometimes they are simply hard to decipher, due to a bad choice of graphical technique or because of poor labelling. Other times, they may be misleading and result in incorrect interpretation of the data. To effectively communicate our results, we need to focus on making good graphs.

Constructing a good graph can be a bit of an art form, but there are some basic principles. Applying these principles puts us on the path to a final graph that is effective in communicating important facts about the data without being misleading. In the above video, Adrian outlines some of these principles. While we adhere to these principles in this course, others might not by accident or to be deliberately misleading. When we talk about the role of ethics in analysis (Activity five) we’ll show some examples of really bad graphs.

You’ve now finished with this first activity! Hopefully you have a greater appreciation for different types of visualisations, when they should be applied, and what we need to consider to make a ‘good’ graph. You now have the opportunity to check your understanding with a quick quiz.

From there, we’ll step through these same graphical techniques and examples to demonstrate how you can also construct them using Excel.