But then we would’ve needed to enlarge the row heights in the table, too. We could’ve enlarged the font size of the check marks and x’s to make them more legible. There were too many diagonal marks all over the page.Īnd they were so small. In other words, they took longer to scan at a glance than the squares. In comparison, creating the squares takes less than a minute because you’re just typing g’s and c’s and then changing the font to Webdings.Ĭheck Marks: Too Hard to Scan at a GlanceĬheck marks and x’s looked too cluttered. Even making the fake version of the table for this blog post took me at least 15 minutes to get right. We used p Shape and make sure they were perfectly aligned within the table. So, we used empty squares to represent variables that weren’t statistically significant and filled-in squares to represent variables that were. We decided to focus on the big-picture findings. Here’s what our final makeover looked like. I’ve got another example of color-coding by category here. In our tables, charts, and maps, Country A was always blue, Country B was always purple, and Country C was always turquoise. Throughout the report, we talked about the differences between the three countries, so we color-coded by country. You should use your own organization’s colors so that your table (and the rest of your publication) will reinforce your brand. We need the results to stand out, and the results can’t stand out if they’re hidden by unnecessary lines.Īnd at the very least, we need to apply color strategically. We kept the horizontal lines, but we changed the black ink to light gray ink. Notice how your eyes can still read down each column without the lines. After, the Bare MinimumĪt the very least, we need to declutter the table. Heck, not even scientists can easily explain p-values! Basically, lower values are better. There were a lot of p-values and decimal places. I made up fake values and hid the names of the variables, but you get the idea. Here’s what the original one-page overview of the study’s results looked like. Then, we launched into the fun stuff, the results! We needed to provide an overview of where the program had been effective (where the treatment group had significantly better outcomes than the control group). Our 30-page report for their leadership began with a short intro about the study. ![]() Then, they did the math to see where the treatment group had outperformed the control group. ![]() They collected data from children, parents, and program staff in both the treatment and control groups. The researchers had spent time on the ground in each country where their programming was offered. Like most in-house research teams, this team had a lot of data. ![]() We wanted to show their leaders where one of their programs for children had been effective. Last year I teamed up with an organization on a custom design project.
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