It's Love Data Week!

What’s that?

Love Data Week is an international celebration of data, taking place every year during the week of Valentine's Day. Nonprofit organizations, universities, government agencies, corporations and individuals are encouraged to host and participate in data-related events and activities.

What’s in it for me?

Lots of free online events, many of which are relevant to nonprofit work such as workshops on data visualization, infographics, data resources, data privacy, etc. See a full list of events HERE.

Where can I learn more?

HERE.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Check Your Data Blind Spots

You’ve heard it before. We see what we want to see. It’s called confirmation bias, and we are all susceptible. Confirmation bias is a big problem to those presenting or consuming data (i.e. all of us.) How can we draw our own and others’ attention to the data that does NOT fit our existing beliefs? How, in other words, can we check our blind spots?

The great thing about your blind spot when it comes to driving is that you know it exists. Your rearview mirrors do not show you an area next to and behind your car. So you learn to check that area in a different way. Experienced drivers do it by rote. Wouldn’t it be great if we also could remember that we have data blind spots and learn to check them automatically?

Here are some ideas for making your blind spots visible. All of them involve doing something before you look at data (in the form of a spreadsheet, table, chart, map, or graph) to help you look at the data with fresh eyes.

  1. Make predictions before looking at data. To prevent seeing only the data that confirm our beliefs, we can make predictions before looking at the data. In Staff Making Meaning from Evaluation Data, Lenka Berkowitz and Elena “Noon” Kuo suggest that, before sharing data with program staff, “have them spend 10 minutes writing down predictions about what the data will say. This exercise helps surface beliefs, assumptions, and biases that may otherwise remain unconscious.” This can involve drawing a predicted trend in the data or jotting down guesstimates of key data points. Then look for differences between your predictions and the actual data and consider:

    • What may have contributed to the differences,

    • What more do you need to know to take action, and 

    • What actions might you consider immediately?

  2. Consider your “null hypothesis” before looking at data. This approach is a variation on strategy number one.  Rather than making a prediction, you pose this question to yourself: If what I expect is NOT true, what might I see? This is analogous to how researchers conduct experiments.  Rather than trying to prove that a hypothesis (e.g. A is affecting B) is correct, researchers aim to collect sufficient evidence to overturn the presumption of no effect, otherwise known as the null hypothesis. It’s sort of like innocent until proven guilty. The idea is to take the opposite view to the one that you hold and then look for evidence to support it. If you can’t find that evidence, then your assumption might be correct. This approach makes you think more critically and perhaps more dispassionately when encountering data.

  3. Set decision criteria before looking at data. “Many people only use data to feel better about decisions they’ve already made,” notes Cassie Kozyrkov in Data-Driven? Think again. To avoid this, you can frame your decision-making in a way that prevents you from moving the goalposts after you’ve seen where the ball landed. Before considering the data, determine your cutoffs for action. For example, you and your colleagues might decide that program participation below 150 in any given month requires investigation and possible action. Let’s say that twelve-month data show participation below 150 in six months. The pre-established cutoff can prevent you from only focusing on the worst months when participation was below 75.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How and Why to Visualize Variability

Every dataset includes variability. The people and things we measure differ from one another in many ways. And visualizing data always involves some decisions about how much of that variability to show. There are tradeoffs:

  1. If you show too much variability, you obscure patterns and trends. To understand anything with data, we usually need to reduce its complexity. We can’t extract meaning from a table full of numbers and letters. So we summarize the data through such activities as grouping people, concepts, and time periods; calculating averages; or organizing individuals or groups in a rank order. This process allows us to detect patterns and trends within the data. Patterns and trends become even more apparent when we visualize the data in the form charts, maps, and graphs by assigning visual cues such as color, size, and shape to groups and values. However, too many colors, sizes, and shapes make discerning the patterns and trends more difficult.

  2. If you show too little variability, you obscure reality*. Overly simplified visualizations do not show just how complex and messy the data actually is. And the viewer may mistake the simplified, summarized version of the data as reality.

You can find a great example of problem #2 in Eli Holder’s article Divisive Dataviz: How Political Data Journalism Divides Our Democracy. He describes the danger of red and blue political maps in the U.S. in this way: “there’s no such thing as a “red state” or a “blue state.” Consider Texas, which is often called a “red” state. In the 2020 presidential election, more Texans voted for Joe Biden (5.26 million) than every other “blue” state, except for California. Even New York, a Democratic stronghold, had roughly 20,000 fewer Biden voters than Texas. . . . While popular election maps accurately reflect the ‘winner-take-all’ dynamic of the electoral college, they create the misimpression that state electorates are monolithic blocks of only-Republicans or only-Democrats.”

And the misimpressions such maps engender have real-world consequences. Holder describes an experiment in which people were shown either dichotomous maps or continuous maps (see examples below). Those shown dichotomous maps were more likely than those shown continuous maps to feel that their state was dominated by one party and thus that their votes mattered less because the election outcome was a foregone conclusion.

So when deciding how many shades of gray or circle sizes to show, consider how much summarization is needed to make patterns and trends perceptible without misleading the viewer with an oversimplified view of the data. Take, for example, these three versions of a map. They each show the same CDC chronic illness survey data with a “diverging color palette” in which blue states ranked high on health indexes; orange states ranked low; and gray states were in the middle. The maps differ in the degree of variability shown. Which map allows you to see corridors of good and bad health without oversimplifying the matter?

*More specifically, the full reality of the data. This 60-second data tip doesn’t get into the nature of reality in general!

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

One Dataset, 100 visualizations

Today’s tip is to check out the 1 dataset, 100 visualizations project. It shows 100 different ways to visualize this simple dataset:

 

It’s fun to compare the different charts and see how they provide different perspectives on the data. For example, to visualize this data, many of us would create a stacked bar chart like this one and call it a day.

 

But look at how this chart allows you to better understand each country’s relative position in relation to number of world heritage sites between 2004 and 2022. We can more easily see, for example, that Denmark leapfrogged Norway.

 

These 100 charts make a strong case for visualizing your data in a number of different ways before selecting one which provides the perspective needed.


To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How To Balance Your Information Diet

Here’s a question for you. And don’t go Googling. Just make your best guess.

Have the number of people experiencing homelessness in the U.S. increased or decreased since 2007?

Whatever your answer, you likely drew on your own personal experience as well as images and information from the media when guessing at the answer. Perhaps you drew on some statistics too. But, unless you have expertise in this area, probably not. Stick with me for a minute, and I’ll not only provide an answer to the question but also some insight into how we consume information.

Personal experience, media, and statistics affect how we understand any issue, and there are limits to each of these inputs. So we would do well to understand those limits before acting on our understanding by voting, donating, or making decisions about programs that our organizations operate. Max Roser’s article in Our World in Data (The limits of our personal experience and the value of statistics) walks us through some of those limitations:

Personal Experience

“The world is large, and we can experience only very little of it personally,” Roser notes. “For every person you know, there are ten million people you do not know.” Even the most social and well-traveled among us can have only a limited understanding of the world through personal experience. I, for example, do not know anyone personally who has been unhoused, and most of my interactions with people in this situation occur on the street when someone asks me for money. This experience provides no information about the breadth of the problem or the range of experiences with this issue over time.

Media

“This fact is so obvious that it is easy to miss how important it is: everything you hear about anyone who is more than a few dozen meters away, you know through some form of media,” Roser points out. “The news reports on the unusual things that happen on a particular day, but the things that happen every day never get mentioned. This gives us a biased and incomplete picture of the world; we are inundated with detailed news on terrorism but hardly ever hear of everyday tragedies like the fact that 16,000 children die every single day.” If I recently heard a story about a city clearing homeless encampments, I may assess the problem as larger, and if I haven’t heard about anything on the issue in awhile, I may assess it as smaller.

Statistics

“The collection and production of good statistics is a major challenge,” writes Roser. “Data might be unrepresentative in some ways, it might be mismeasured, and some data might be missing entirely.” But, unlike personal experience and the media, it provides a way of assessing the full range of an issue. So it’s important to add statistics, along with personal experience and the media, to our information diet.

To add some statistics to your understanding of homelessness, the number of people experiencing homelessness in the U.S. decreased from about 650,000 in 2007 to about 580,000 (about 18 of every 10,000 people) in 2022 according to The 2022 Annual Homelessness Assessment Report to Congress.

We should not discount personal experience, the media, or statistics because of their limitations. But we should appreciate their limitations when forming opinions and taking actions based on them. As Roser notes: “Each way of learning about the world has its value. It’s about how we bring them together: the in-depth understanding that only personal interaction can give us, the focus on the powerful and unusual that the news offers, and the statistical view that gives us the opportunity to see everyone.” As described in many tips in this blog, well-designed charts make data/statistics more accessible to everyone and thus allow everyone to see everyone.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Why You Should Know About Beeswarm Charts

If you are looking to compare individuals, programs, locations, events, etc. on one or more measures, a beeswarm chart could be just the ticket.

This is a new addition to a series of tips on different chart types. In each tip, l give you need-to-know information in a format akin to the “Drug Facts” on the back of medication boxes: active ingredients (what the chart is), uses (when to use it), and warnings (what to look out for when creating the chart). The idea is to fill up your toolbox with a variety of tools for making sense of data. To learn about other chart types, check out this index of data tips.

Active Ingredients (What is a beeswarm chart?)

A beeswarm chart (or swarmplot) is a type of data visualization that displays individual data points so that they don't completely overlap, resulting in a "swarming" effect. The beeswarm chart is related to strip plots and jittered strip plots, both of which are scatter plots with a measure on the vertical axis and a category on the horizontal axis. Strip plots become less useful when tightly packed data points start to overlap too much, obscuring patterns in the data. The jitter plot partly solves the problem but not as well as the beeswarm chart.

Uses

Beeswarm charts are useful to highlight individual categories or entities while still showing a distribution as a whole. In the example above, you can see that family events and smaller events were the most highly rated, while health events and larger events generally got lower ratings and that the distribution of average ratings was similar for introduction, beginner, intermediate, and advanced level events.

This type of chart is not native to most data viz applications but happily there is a free online tool called AdvViz that allows you to upload a CSV file to create a basic beeswarm chart and then download it as a Tableau file. From there, you can open it in Tableau Desktop and make adjustments to the formatting. That’s how I created the beeswarm chart above. You can also create this type of chart in Flourish and RAWGraphs.

Warnings

In the example above, I used color to distinguish different event types and circle size to show the number of participants in each event. When using color coding, make sure the colors contrast enough so that viewers can easily discern one category from another. Also, reducing the opacity of the color allows viewers to see overlapping circles. When using size to show a measure, make sure that the range of the measure is wide enough that the viewer can easily discern small from large. Small differences in size can be hard to detect.

Fun Fact

A beeswarm chart is a great way to show stressors on bee colonies! See chart below.

Source: Data Literacy


To see past data tips, including those about other chart types, scroll down or click HERE.

Sources: The Data Visualisation Catalogue

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Best Data Viz of 2023

Looking for a fun (if somewhat geeky) study/work break? Check out these best-of lists for 2023:

New York Times

Visual Capitalist

538/ABC News

FlowingData

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Top 10 Tips of 2023

Here are the top ten reader favorites in case you missed them . . .

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How To Activate Board Member Fundraising With Visuals
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Free Interactive Viz For You: Giving in the U.S.
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Nonprofits Need This Dashboard
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Jitter Your Charts
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Bar Chart Hack #7: The Lollipop Chart
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Bar Chart Hack #6: The Funnel Chart
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Bar Chart Hack #5: A Little Fine-Tuning Can Transform A Chart
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Bar Chart Hack #3: The Combo Chart
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Ideas You Should Steal From This Viz (Installment 7)
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Data Viz Resources You Should Know: Data Visualisation Catalogue
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How To Activate Board Member Fundraising With Visuals

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Upcoming Data Viz Workshops

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Free Interactive Viz For You: Giving in the U.S.

As we move into gifting season, I thought I’d toss out a gift to you. It’s a quick interactive viz that you can employ however you see fit. Use it in a website, presentation, or social media post to rightsize folks’ understanding about the state of charitable giving in the U.S. and, perhaps, help to turn the tide. For the link address or embed code, click on the share icon below.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Nonprofits Need This Dashboard

Does your nonprofit have participants (or volunteers or clients or human beings of another sort) in various programs? If so, you could benefit from a dashboard like this one (see below). Give it a spin. Select a program at the top to highlight participants in that program in the charts. This dashboard allows for easy comparisons across programs, across statuses (e.g. enrolled, waitlisted, and withdrawn), and across time. Scroll over charts to learn more.

My inspiration for this dashboard came from Eve Thomas at The Data School. Check out Eve’s article, which includes instructions for creating this type of dashboard with Tableau (assuming basic Tableau knowledge.)

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

The Pies That Bind

Reposted from November 2022

Rather than provide you with a tip, I thought I’d start this holiday week by offering you a little hope instead. It’s pie season, and folks are searching for pie recipes on Pinterest. According to this Food & Wine article, Pinterest analyzed internal search data to discover the most common pie recipe search terms in each state. I took that data and mapped it. As you can see below, pie preferences do not appear to fall along regional, ideological, or even agricultural lines. Minnesotans love lemon pie, and Floridians love pumpkin pie, although I’m guessing that more lemons are grown in Florida and pumpkins in Minnesota. Some states were idiosyncratic in their searches. Hello West Virginians who love no-bake peanut butter pies and Kentuckians who love pies made with cushaws, a type of squash I’d never heard of. But most states shared pie interests with other states. So this Thanksgiving, let’s be thankful for our shared love of pie. Scroll around on the vizes below and Happy Thanksgiving!

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

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Hi, I'm Amelia.

Not Your Grandmother's Icons

We have all seen icon charts that look like this (even if our grandmother didn’t create them):

Want to make an icon chart that actually looks like real people as in the example below? Well, of course, you can just find some cool silhouette icons and use any graphic design program — such as Canva or Adobe Illustrator —  to layout and color icons as you wish. However, if you want the chart to be interactive, you will need to use a program like Tableau or Power BI. I created the chart below in Tableau. It provides more information when you scroll over the icons. Scroll down for Tableau instructions.

Here’s how I did it:

(Note: These directions assume basic knowledge of Tableau. If you don’t have that knowledge, here’s a good video on Tableau basics.)

  1. I selected 10 head silhouettes to use as icons. You can find great (free) icons on sites like flaticon , The Noun Project, or Canva. Be sure to save each icon as a separate PNG file with a transparent background.

  2. I added the icons to the shapes folder in my Tableau Repository. Here’s a short video on how to do that.

  3. I connected a data file (such as an Excel or CSV file) to Tableau Public (the free version of Tableau). The file included 40 rows, one for each applicant, and columns for:  a unique identifier for applicants (such as an ID number), selection status (whether applicants was or wasn’t selected to be a participant, and 3) the silhouette image assigned to the applicant.

  4. In Tableau, I started a new worksheet, changed the marks type to shape, and dragged:

    1. The ID number to the columns shelf (note that ID number should be a dimension not a measure);

    2. The selection status dimension to color on the marks card; and

    3. The silhouette dimension to shape on the marks card.

  5. I clicked on shape on the marks card, clicked on “Reload Shapes,” selected the shape palette that I added to my Tableau Repository in Step 2,  assigned head shapes to the various values for the silhouette dimension., and then clicked “OK.”

  6. I clicked on color on the marks card and adjusted the colors for the “selected” and “not selected” values.

  7. I dragged ID number to the filters shelf and selected ten ID numbers to show.

  8. I changed the view from standard to entire view and clicked on size on the marks card and adjusted the size of the heads as I preferred.

  9. I hid the header and title, duplicated the worksheet, and selected different IDs using the filter. I then repeated this step to create two more worksheets.

  10. I created a dashboard, added a vertical container, dragged the four worksheets into the container, clicked on the drop down menu for the container (in the upper right corner of the container) and selected to distribute contents evenly. I then adjusted the layout by adding outer padding and added in a text box.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Ideas You Should Steal From This Viz (Installment 10)

Here’s another steal-worthy viz to inspire you. There’s so much I like about this data dashboard created by Alessia Musìo on Tableau Public. In the Information is Beautiful Awards submission for this dashboard, Musìo notes: “Simplicity, coherence, and clarity are the words that have guided me in the development of the project.”

Here’s what I especially like and suggest you apply to your own dashboards:

  • User friendly: There’s no need for a user guide for this dashboard. The simple left-hand panel tells you all you need to know: how to navigate to other pages, how to filter the data, and how to interpret the color coding.

  • Limited views of data: There are only two ways of looking at the data contained in the dashboard: in a map which allows you to make comparisons across regions and countries or in a chart showing change over time. And there are limited ways to filter the data. This simplicity makes the dashboard more approachable and instantly usable.

  • Methodology and sources page: For those interested, the methods and sources are presented in an organized way with links.

Take the dashboard out for a spin. Be sure to hover over the circular elements on the single country charts to see comparisons with countries of the same continent.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Data Dashboard Treasure Hunt

Looking for a way to engage your staff, board members, and others in your data dashboard? Want them to understand how to use it and how it can inform their work? Here’s a great idea from MiraCosta College: a dashboard treasure hunt! Each page features one page of the dashboard along with questions that require the user to interact with the dashboard. Correct answers lead the user toward a hidden treasure. Try it for yourself:










Source: Treasure Hunt by MiraCosta College on Tableau Public

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

How to Extract Meaning from Survey Data

You just conducted a survey of your clients. participants, board members, visitors, or community members, and chances are you used some Likert Scales in that survey. In other words, you asked respondents to state their level of agreement or disagreement on a symmetric agree-disagree scale. A typical 5-level Likert scale is:

Strongly Disagree - Disagree - Neither Agree nor Disagree - Agree - Strongly Agree

Here’s a FAQ (which is more like a QYSA: Questions You Should Ask) on visualizing Likert Scale data to extract useful information.

Have you collected data just once or multiple times with this survey?

If this is a one-time deal, then I would suggest that you visualize the data using a stacked bar chart. Exactly which type of stacked bar chart depends on what you are trying to understand and show. Check out this Daydreamming With Numbers blog post: 4 ways to visualize Likert Scales. It walks you through various options. If you have collected the data two or more times, read on.

Should I calculate average scores and compare them?

A common way to look at change over time with Likert Scale data is to assign numerical values to each response (e.g. Strongly Disagree: 1, Disagree: 2, Neither Agree nor Disagree: 3, Agree: 4, Strongly Agree: 5) then calculate the average across respondents at two or more points in time and compare them. Some may even use a statistical test (such as a paired sample t-test) to assess whether the averages are “significantly” different. This may seem like an obvious way to deal with the data, but there are problems with it:

  • The distance between 4 and 5 is always the same as the distance between 2 and 3. However, the distance between Agree and Strongly Agree is not necessarily the same as the distance between Disagree and Neither Agree nor Disagree. So we may be distorting respondents’ opinions and emotions by assigning numbers to these response options.

  • Respondents are often reluctant to express strong opinions and thus gravitate to the middle options. Averaging a bunch of middle options (2, 3, and 4) only amplifies the impression that respondents are on the fence.

  • Averages do not give us a sense of the range of responses. The average of these 4 responses (5,1,1,1) is the same as the average of these 4 responses (2,3,2,1). Also averages result in fractional results which can be hard to interpret. Does an increase from 4.32 to 4.71, even if it’s statistically significant, really mean anything in the real world? At best, we can say that the aggregated results changed from somewhere between Agree and Strongly Agree to another place that is a little closer to Strongly Agree.

What are alternatives to calculating averages?

Visualize the spread of responses. If you don’t have too many questions (or can group questions together) some simple side-by-side stacked bar charts might do the trick. See sketch 1 below.

Use the mode or median rather than average.The mode is the number that occurs most often in a data set and may be a good way to describe the data if one response dominated. The median is the middle value when a data set is ordered from least to greatest. If responses tend toward one end of the scale (i.e. are skewed), it may be more reasonable to use the median rather than the average. If you feel that the assumption of equal spacing between response options is legit, then you might stick with the average.

Visualize average, mode, or median using one of the following chart types (see sketches 2-4) to understand and show change over time.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Data Viz Resources You Should Know: Our World In Data

Our World in Data is a new addition to my highly-curated resources list. I occasionally write a 60-second data tip describing a particular resource, including why I think it’s cool. And I link each of these tips to a resources list on my website.

What is it?

Our World in Data is a collection of charts and articles on “the world’s largest problems”. They believe making knowledge, which “is often stored in inaccessible databases, locked away behind paywalls and buried under jargon in academic papers” more accessible to foster progress.

Who’s it for?

Anyone trying to better understand the world and how it’s changing including individuals, journalists, researchers, and policymakers. Our World in Data’s charts and data can be freely downloaded and embedded in others’ work.

Who’s behind it?

Our World in Data is a collaborative effort between researchers at the University of Oxford, who are the scientific editors of the website content, and the non-profit organization Global Change Data Lab (GCDL) which publishes and maintains the website. Max Roser is the founder and director of Our World in Data. He began the project in 2011 and for several years was the sole author until receiving funding for the formation of a team.

Why I think it’s cool

Their charts and articles help to correct our misperceptions that all global living conditions are getting worse. In their words, “historical data and research shows that it is possible to change the world. Historical research shows that until a few generations ago around half of all newborns died as children. Since then the health of children has rapidly improved around the world and life expectancy has doubled in all regions. . . . Progress is possible, but it is not a given. If we want to know how to reduce suffering and tackle the world’s problems we should learn from what was successful in the past.”

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

Without Data Viz, You Can Get It All Wrong

The aim of today’s tip is to remind you of the importance of visualizing data. Without charts, maps, and graphs, we can get it all wrong. We base our understanding on a few stories in the media, on the experience of someone we know, or on what we hear most often about the topic rather than on what is actually happening. More on this in a moment. First, please take this short pop quiz and then scroll down.

 

“Stories about individual people are much more engaging – our minds like these stories – but they cannot be representative for how the world has changed,” writes Max Roser. “To achieve a representation of how the world has changed at large you have to tell many, many stories all at once. . . .“

Roser made the series of charts below to tell all of those stories in a way that we can understand. It shows the number of people out of 100 with various experiences over the course of 200 years. It’s worth checking out Roser’s whole article entitled “The short history of global living conditions and why it matters that we know it.”

I’ll leave you with one more quote from Roser: “The result of a media – and education system – that fails to present quantitative information on long-run developments is that the huge majority of people is very ignorant about global development and has little hope that progress against serious problems is even possible. Even the decline of global extreme poverty – by any standard one of the most important developments in our lifetime – is only known by a small fraction of the population of the UK (10%) or the US (5%). “

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

The Allure and Danger of Data Stories

Reposted from December 2018

I recently read Has Data Storytelling Reached Its Peak? in which Amanda Makulec suggests that we use the term “data storytelling” cautiously. “Not every piece of data needs to be communicated as a story,” Makulec notes. “Sometimes we need to start with story-finding or just a well structured chart, rather than a full narrative arc.” I’ve had my own concerns about the term “data storytelling” which I’m sharing with you (again) today.

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“Data” and “storytelling” are an item. You see them together all the time lately. When I first came across the term “data storytelling,” it instantly appealed to me. “Data” suggests credibility, information that has some objective basis. But data, to many of us, is boring. Its meaning is often uncertain or unclear. Or, even worse, it’s both. “Storytelling,” by contrast, suggests clarity, a plot with both excitement and resolution. So, by coupling these two words, we seem to get the best of both worlds. Data lend credibility to stories. Stories lend excitement and clarity to data.

Indeed, that’s the point of data storytelling. As Brent Dykes, a data storytelling evangelist of sorts, noted in a 2016 Forbes article, “Much of the current hiring emphasis has centered on the data preparation and analysis skills—not the ‘last mile’ skills that help convert insights into actions.” That’s where data storytelling comes in, using a combination of narrative, images, and data to make things “clear.”

But let’s step back just a minute. Why are we so drawn to stories? According to Yuval Harari, author of Sapiens: A Brief History of Humankind, the answer is:  survival. Harari maintains that humans require social cooperation to survive and reproduce. And, he suggests that to maintain large social groups (think cities and nations), humans developed stories or “shared myths” such as religions and corporations and legal systems. Shared myths have no basis in objective reality. Reality includes animals, rivers, trees, stuff you can see, hear, and touch. Rather, stories are an imagined reality that governs how we behave. The U.S. Declaration of Independence states: “We hold these truths to be self-evident: that all men are created equal . . . “ Such “truths” may have seemed obvious to the framers, but Harari notes that there is no objective evidence for them in the outside world.  Instead, they are evident based on stories we have told and retold until they have the ring of truth.

So stories (in the past and present) are not about telling the whole truth and nothing but the truth. Instead, they are often about instruction: whom to trust, how to behave, etc. And we should keep this in mind when telling and listening to “data stories.” To serve their purpose, stories leave out a lot of data — particularly data that doesn’t fit the arc of the story. For example, you might not hear about a subgroup whose storyline is quite different from the majority. Or, indeed the story might focus exclusively on a subgroup, ignoring truths about the larger group.

Bottom line: listener beware. A story, whether embellished with data or not, is still just a story. And truth can lie both within and outside of that story.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.

New and Improved Stacked Bar Chart

Here’s a simple solution to a problem with stacked bar charts. Yes, they allow you to compare the size of different groups as well as the subgroups within each group. But comparing the subgroups is tough because — for all but one of the subgroups — you have to compare the length of the bar segments without a common baseline.

The bar chart below, created with Tableau, solves that problem by adding a filter so that you can see the whole bars by selecting “All” but also see only one or more subgroups so you can easily make comparisons across just those subgroups. In this chart, I’ve also set the sort order so that it’s always in descending order regardless of the filter selections. See info below on how I set the sort order in Tableau.

See how this chart works by interacting with it yourself! Change the selections on the checkboxes.

To sort questions in descending order regardless of the response option chosen, click the dropdown arrow on Question in the rows shelf and select Sort . . .

. . . .Then choose to sort by Field in descending sort order and choose the name of the field that indicates number of respondents.

To see past data tips, click HERE.

Let’s talk about YOUR data!

Got the feeling that you and your colleagues would use your data more effectively if you could see it better? Data Viz for Nonprofits (DVN) can help you get the ball rolling with an interactive data dashboard and beautiful charts, maps, and graphs for your next presentation, report, proposal, or webpage. Through a short-term consultation, we can help you to clarify the questions you want to answer and goals you want to track. DVN then visualizes your data to address those questions and track those goals.