Critical Thinking for Data Storytelling

Introduction

Most forms of storytelling follow a narrative arc. The most common narrative arc is structured in three parts. First comes the setup, which helps put the issue in context. Then comes the conflict or tension and finally, there is the resolution. When looking to create a data story you want to be able to transmit something of value to your audience. But how do you get started? Where do you find a story that is worth telling? A good way to start is by exploring critical thinking.

Critical thinking is a fantastic way of obtaining interesting questions because it forces you to question your own beliefs, your own assumptions, and your own internal biases about the issue at hand. By doing so, this enables you to ask more interesting questions. In turn, asking more interesting questions allows you to develop more interesting insights. Insights that give you an advantage over others and insights that help deliver real value to your audience. But then, how do you apply critical thinking and where do you start? Glad you ask.

Getting Started

There are two components required for thinking critically about a statement or expression. One is an idea that you express. The other is reasoning, which is your beliefs, or experience that supports the conclusions you have about that idea. For instance, eating junk food is bad for your health. In this case, eating junk food is the idea and bad for your health is the reasoning.

Once you have established your reasoning and the idea that’s behind the reasoning, you can begin to ask deeper questions. A good rule of thumb is to follow with the threes: the What? the How? and the Why? What is the research saying? And how do you know? For instance, how do you know junk food is bad for your health? and finally, why? Why do you know it’s not good for you?

Challenge Your Own Beliefs

By asking these questions you are challenging your own assumptions about the idea and reasoning and you are able to gain new perspective on the ideas that you have as opposed to blindly accepting them.

This is what critical thinking does. It forces you to look at the reasoning behind your statements. By asking the questions you can gain new reasoning. For instance, how do I know junk food is bad for your health? I know because obesity and diabetes is high among people who eat junk food on a regular basis. As a result, junk food must be bad for your health. Be on the look out for these words, because and as a result as these tend to imply that reasoning will follow.

Again, the great thing about critical thinking is that it helps question your own ideas. By questioning your own ideas you can come up with better questions. Not only with better questions but it can also help expose the blind spots in your reasoning. Continue questioning until you arrive at answers you were not expecting. This way you can create stronger and sounder data stories that leaves your audience wanting more.

Exploring Possible Stories With Quadrigram

Similar to exploring a blank canvas, beginning a data story can be daunting at first. The good thing is that you don’t really need to have questions to begin creating. All you need is a dataset and from here you can begin exploring.

In the image above, we see a dataset for a complete list of NBA players by state. We also have other columns such as games played, field goals, free throws, assists, personal fouls, their city of birth, and coordinates. I want to see which cities are repeated the most.

With Quadrigram I can do this by adding the excel spreadsheet to the editor and configuring the tables directly from the editor.

I’ve decided to aggregate players by city with Quadrigram, so now my table shows cities by players repeated by that same city.

What I’ve done is create a bar chart to help me visualize where most NBA players come from. Now, I’m not going to be using this for my data story but I will be using this chart for personal use. I’m able to focus in on areas that I want to further explore. I can see that Chicago has the highest concentration of NBA players. That makes sense. Chicago is a large city with a high urban population.

So now, I’m able to shift my question. Rather than looking at where all NBA players come from, I want to focus on where NBA players come from by city. So I can filter and make changes in my spreadsheet by applying formula function. I want to see statistics for NBA players by city. From here, I can begin working on a data story.

 

The idea is that once you have the results, you can begin digging deeper by questioning the line of reasoning by either communicating a deeper sense of reasoning or communicating a way that questions this line of reasoning in a way that is backed by data.  There are many ways to do this and critical thinking and exploring with data is one way to get started.

 

 

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