The presentation of data in tables is a usual practice in scientific talks. Sadly, most tables are ineffective. In this first installment, I give an example of before and after table design.Writing about tables is something I wanted to do for long time, after all quantitative data is at the heart of science and its communication. Tables are ubiquitous, and if you are like me, you learned how to design them by imitation. The problem is, most tables suck, as illustrated in this quote
Getting information from a table is like extracting sunlight from a cucumber.
— Farquhar & Farquhar, 1891
Tables should communicate, but instead they are used as a dump of tabular data, which the audience is supposed to navigate through, understand and make sense of. Oh yeah, all of that in a couple of minutes.
Let's dive in. Before considering showing a table at a talk, ask yourself, "so what?". Does it support your point? Does it prove someone's else point wrong? You might want to write down 2 or 3 questions that the audience should be available to answer after you have shown and commented the table. If you can't think of any question, or if they sound stupid to you, drop the table, because it doesn't move your talk forward. After you have done with the table, ask another set of questions about the retrieval of information in the table. Let's look at the example of Wainer.
- What are the principal causes of accidental death?
- Which are the most frequent? Which the least frequent?
- Are there any unusual interactions between country and cause of accidental death?
- How do the countries differ with respect to their respective rates of accidental death?
What Wainer has done is to highlight the data by partly reducing the non-data ink and enhancing the data ink. In other words Wainer must have asked himself
"Would the data suffer any loss of meaning or impact if this were eliminated?"
— Stephen Few, author of Show Me the Numbers.
and where the answer was no, he got rid of it.
In addition to improving the data ink in the table, Wainer has
- reordered the rows and columns in a way that makes sense to the audience
- added statistics that summarize the data
- clustered the data
- and, finally, rounded the figures.