Leave a Reply

Your email address will not be published. Required fields are marked *

Maybe you’re already familiar with dot plots…

Maybe you’re already using them…

Maybe you can make ’em in your sleep…

Or maybe you have no idea what I’m even talking about! (If that’s the case, stick around! This video is for you.)

You’ll learn about the differences between clustered bar charts and dot plots. Then, you’ll see a real-life example so you can start thinking about how you’d apply these in your own workplace.

Transcript

Ann K. Emery: [00:00:00] Maybe you’re already familiar with dot plots. Maybe you’re already using them. Maybe you can make them in your sleep.

Or maybe you have no idea what I’m even talking about! If that’s the case, stick around. This video is for you.

You’re going to learn about the differences between clustered bar charts and dot plots.

And then I’ll show you a real life example. So you can start thinking about how you might apply this chart type to your own workplace.

I’m Ann Emery. You’re watching Dataviz on the Go, the series where I make quick tutorials as I’m racing around between workshops and webinars and conferences and consulting projects.

And speaking of consulting projects, I was recently in a meeting with a client and they were asking about these chart types, clustered bar charts and dumbbell dot plots.

And right away when you look at them, they’re obviously different! One’s got bars, one’s got dots, but there is a slight, smaller nuance that I want to draw your attention to here. [00:01:00] And that’s related to attention!

It’s related to where our eyes and brains, and therefore where our precious attention, goes when we look at each of these graphs.

So when you look at a bar chart, your eyes are going to look at obviously the end point, right? That’s the really juicy part of the bar chart.

With dot plots, they don’t waste any time. They cut right to the chase. I love them for their brevity and they just plot the end point. Okay, they don’t waste our ink and waste our time with all this, all this unnecessary ink.

Another slight difference is when you want to compare the end points, you have to do a little bit of a diagonally down movement to compare them, where dot plots plot everything on the same plane, so that it’s just a little bit faster, right?

Instead of stacked endpoints, it’s side by side: same line, same plane.

Alright, let’s look at a real life example because [00:02:00] this one with A, B, C, D and group one and group two is obviously super made up!

Let’s go back into the vault in my memory, where about 15 years ago, which is a million years ago, I was working on a lot of school climate surveys.

I did a lot of consulting for the U S Department of Education. I looked at test scores, all sorts of academic performance and school climate surveys, and I don’t remember the exact details of how this was measured, but I do know that we surveyed parents. And school staff, like the teachers and the principals and all the administrative staff. And then we compared how they responded on different measures.

This is the default graph that Excel is going to give you, which of course, if you’ve watched any of my other YouTube tutorials or read any of my blog posts over the years, you know, we can’t keep that. Okay. Let me just let, you know, just make it super duper clear what we’re not doing.

We’re not keeping these default, inaccessible settings. At a bare minimum, we’re going [00:03:00] to add Big A Accessibility –508 compliance and ADA compliance. That’s the usual stuff. That’s like making sure the font is big enough and dark enough, removing the legend and adding the direct labels right here, which is a win for grayscale printing and for custom words. Colorblindness.

And then we might even, I hope, I hope you do this. I hope you keep going with “little a accessibility” edits to make sure that your graph is really intuitive.

That’s going to be things like grouping, right? Finding groups of elements where parents scored the school higher, versus staff.

That’s going to be things like adding annotations, which, guess what? That’s just a good old text box. It’s a call- out box to help people figure out what the patterns are so that they’re not just guessing and searching and hunting for any type of insight.

This one, honestly, when it’s Big A and little a accessible, I’d say [00:04:00] it’s not that bad!

I wouldn’t lose sleep over this.

If you go this far with editing with your clustered bar charts, I’m going to say: virtual high five, leave it alone. You’ve graduated. No need to keep on going with editing unless you want to, unless you’re ready to really keep boosting your skills and try out something that’s a little bit more advanced.

And that advanced, uh, approach would be the dumbbell dot plot. Which as you know, only puts the emphasis on the end point, the juicy important part. And it helps draw your attention with this connecting line, the, the dumbbell part of it to the difference between the staff and the parents- or whatever groups you’re comparing in your project.

Now, you’re going to have to put the annotations on these finished charts in a little bit different spot, depending on whether you’re doing a landscape final project or a portrait final project.

So if this was going to be landscape, you’re going to have [00:05:00] space for the annotations off to the side. If it’s portrait, It’s going to be a lot narrower.

You’re just not going to have the space. So you’re probably going to have to put the call out boxes above each chart, something like this.

Here’s what I mean: landscape versus portrait. You’re just going to have to think very carefully about where everything fits. So it’s not so condensed that people can’t actually notice those important differences between your groups.

It’s your turn. Comment below this video. Let me know, are you using dot plots? For what? You probably aren’t doing school climate surveys. You’re probably using them for something completely different from this. And also let me know what types of how to questions you have. These are possible in good old Excel and PowerPoint and Word, but they require some advanced behind the scenes magic tricks to make them happen, which I am happy to share with you in future [00:06:00] videos.

More about Ann K. Emery
Ann K. Emery is a sought-after speaker who is determined to get your data out of spreadsheets and into stakeholders’ hands. Each year, she leads more than 100 workshops, webinars, and keynotes for thousands of people around the globe. Her design consultancy also overhauls graphs, publications, and slideshows with the goal of making technical information easier to understand for non-technical audiences.

Leave a Reply

Your email address will not be published. Required fields are marked *

You Might Like

Our complimentary mini course for beginners to dataviz. Takes 45 minutes to complete.

Enroll

Breaking Barriers with Accessible Data Visualization

This is a short listen (15 min) with some techniques that are hopefully super obvious if you’ve been following my work for a while.

More »

Inside our flagship dataviz course, you’ll learn software-agnostic skills that can (and should!) be applied to every software program. You’ll customize graphs for your audience, go beyond bar charts, and use accessible colors and text.

Enroll

Subscribe

Not another fluffy newsletter. Get actionable tips, videos and strategies from Ann in your inbox.