5 Comments

  • danawanzer says:

    I love the dot-plots. I have had issues in the past trying to do them and adding the values inside the dot. I prefer how you did it because it fixes the issue I had: if the dots are too close together, how do you show the values? This makes it so much easier to understand. Now I have to go tinker with another graph of mine…

    • Ann K. Emery says:

      Yes, I’ve run into the same issue. My first choice is to place the labels on top of the tiny dots (so there aren’t actually dots showing at all, just the numbers or percentages — very sleek!). But some datasets have values that fall so close together, and then everything gets smushed, so I’ll arrange the labels to the left or right. In later editing stages of the document, I make sure all the dots plots have the exact same format, i.e., you wouldn’t have one dot plot with labels on top of the dots and another with labels to the left and right.

  • Excel says:

    Hi Danawanzer, I loved the content of your blog, I have a project in Brazil, and my students are loving their tips and posts. Thank you for the lovely work of helping!

  • Marie says:

    I love this! Thank you for including the steps in your design process and how you tried different things that led you to the final result.

  • Leave a Reply to Excel Cancel reply

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    How to Visualize Survey Data with Check-All-That-Apply Questions

    Updated on: Jun 8th, 2017
    Data Visualization
    , , , , , ,

    Most of the surveys I’ve designed, analyzed, and even taken have included a check-all-that-apply question. Today’s post includes three ideas for visualizing those survey questions and a bunch of transparency about my own mistakes along the way.

    The Survey Questions

    Last month I spoke with Harvard University graduate students about visualizing survey results. This is one small portion of their survey.

    Here are the check-all-that-apply survey questions that I wanted to graph.

    My First Attempt

    I started by visualizing the first question.

    • I’m pretending that 30 people completed the survey. I focus on raw numbers of people when I’m dealing with smaller numbers (less than 100) and I convert numbers into percentages when I’m dealing with larger numbers (greater than 100). You’ll notice that the scale along the bottom intentionally goes from 0 to 30 people rather than from 0 to 100 percent.
    • Once in a while, when I sense that the audience is really hungry for details, I’ll also include percentages alongside the raw numbers. In Excel, I simply concatenated the values from a few cells together.
    • I built stacked bar charts instead of regular bar charts because I wanted to remind viewers that while some people checked the survey boxes (dark blue) others did not (light blue). I only labeled the dark blue bars because that’s the segment that really matters.
    • Rather than following the order of questions from the survey (super boring), I listed the items from greatest to least (more useful).
    • I outlined the dark and light segments in white to provide just the right amount of distinction between categories. White outlines also make printing look a hair crisper.
    • I deleted all the garbage (borders, grid lines, and so on).

    Visualization of a survey question using a stacked bar chart.

    I flew through the visualization of the first question and bolted just as quickly into the second question. Within minutes, I had built this one-pager that the researchers could pass around at a meeting.

    One page visualization of survey questions that researchers could pass around at a meeting.

    Oops! My Second Attempt

    Then, at the very end, I took a moment to actually read the survey questions. You know, that thing you should probably do first. The categories looked familiar. Too familiar. Eerily familiar. I wondered, Didn’t I already read about ‘industrial and Naval history?’ I think ‘studio art and graphic design’ sounds familiar, too… 

    In my zest for building the graphs, I had forgotten to think strategically about the page layout. Would viewers want to read about the survey respondents’ prior academic experience first, and then read about respondents’ prior work experience second? Probably not. Viewers could care less about the order that you asked questions on the survey. There’s always a better way to order your results than by the order in which you asked the questions on the survey. Viewers were probably trying to design museum exhibits by topic–were visitors already familiar with American history?

    How? Through their work experience or academic experience? In this second draft, I rearranged the page by topic instead of by survey question.

    One page visualization that has been rearranged by topic instead of by survey question.

    Oops! My Third Attempt

    Then, I took another moment to reflect, and was disgusted by the stacked bar charts I had designed. Clustered bar charts are my least favorite chart of all time because 1) there’s (almost) always a more effective alternative but 2) despite these alternatives they’re used over and over and over and over and over.

    In this scenario, dot plots are the better choice because they align the academic experience and work experience numbers on the same plane. If I want viewers to compare academic experience and work experience, then it’s my responsibility to place those numbers as close as physically possible to each other. They also take up less ink and space on the page. It’s cheaper to print little dots than big rectangles. You save viewers’ energy and trees; everybody wins.

    One page visualization using dot plots.

    Bonus: Download the Materials

    If you want to explore how I designed the stacked bar charts, the clustered bar charts, the dot plots, or the handouts, you can purchase the templates here:


    Purchase the templates

    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.

    5 Comments

  • danawanzer says:

    I love the dot-plots. I have had issues in the past trying to do them and adding the values inside the dot. I prefer how you did it because it fixes the issue I had: if the dots are too close together, how do you show the values? This makes it so much easier to understand. Now I have to go tinker with another graph of mine…

    • Ann K. Emery says:

      Yes, I’ve run into the same issue. My first choice is to place the labels on top of the tiny dots (so there aren’t actually dots showing at all, just the numbers or percentages — very sleek!). But some datasets have values that fall so close together, and then everything gets smushed, so I’ll arrange the labels to the left or right. In later editing stages of the document, I make sure all the dots plots have the exact same format, i.e., you wouldn’t have one dot plot with labels on top of the dots and another with labels to the left and right.

  • Excel says:

    Hi Danawanzer, I loved the content of your blog, I have a project in Brazil, and my students are loving their tips and posts. Thank you for the lovely work of helping!

  • Marie says:

    I love this! Thank you for including the steps in your design process and how you tried different things that led you to the final result.

  • Leave a Reply to Excel Cancel reply

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

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