Smooth and Rough on the Highways of France

In a previous post I suggested that historians should use quantitative methods less to answer existing questions than to pose new ones. Such a digital humanities (DH) approach would be the reverse of the older social science history approach, in which social science tools were use to “answer” definitively longstanding questions. This post offers another example […]

Fearbola, Ebola and the Web

My nasty “cold” has been diagnosed as Influenza A, so it’s bed rest for 48 hours. And, of course, blogging about why Ebola gets all the news but not good ‘ol killers like influenza. I got CDC figures for deaths and then ran Google searches for the related terms, totaling the number of hits. I was […]

Visualizing Ebola

The Guardian recently posted a dataviz comparing Ebola to other infectious diseases. It’s from a forthcoming book entitled Knowledge is Beautiful and it is indeed beautiful. Unfortunately, it’s a really bad viz. Below is my alternative viz (using the Guardian’s data), along with a critique. The basic issue is evolution. Because viruses reproduce quickly so they’re a great […]

Data illustration vs. data visualization?

Just discovered a great blog post on “data illustration” versus “data visualization” at Information for Humans. AIS argues that data illustration is “for advancing theories” and “for journalism or story-telling.” By contrast data visualization “generate[s] discovery and greater perspective.” I love this distinction, although I’m not sure I like the specific language. Tukey famously argued […]

Build great models . . . throw them away

The rise of digital humanities suggests the need to rethink some basic questions in quantitative history. Why, for example, should historians use regression analysis? The conventional answer is simple: regression analysis is a social science tool, and historians should use it to do social science history. But that is a limited and constraining answer. If […]

Back to Basics

Aaron at Plan Space from Outer Nine has a valuable insight about how standard statistics textbooks often favor technique over understanding. I think we could extend approach this from “central tendency” to the broader question of “association.” We tend to view various measures of association  (for example, Chi-square χ2, Spearman’s rho ρ, Pearson r, R2, etc.) […]

In praise of “Shock and Awe”

Why graph? And why, in particular, use innovative and unfamiliar graphing techniques? I started this blog without addressing these questions, but a recent blog post by Adam Crymble, critical of “shock and awe” graphs made me realize the need to explain EDA (Exploratory Data Analysis) and data visualization. Crymble wisely challenged data visualization practitioners to […]