My previous post pondered the term disestimation, coined by Charles Seife in his book Proofiness: How You’re Being Fooled by the Numbers to warn us about understating or ignoring the uncertainties surrounding a number, mistaking it for a fact instead of the error-prone estimate that it really is. Sometimes this fact appears to
Author
Errors, lies, and big data
The Chicken Man versus the Data Scientist
In my previous post Sisyphus didn’t need a fitness tracker, I recommended that you only collect, measure and analyze big data if it helps you make a better decision or change your actions. Unfortunately, it’s difficult to know ahead of time which data will meet that criteria. We often, therefore, collect, measure and analyze
Sisyphus didn’t need a fitness tracker
In his pithy style, Seth Godin’s recent blog post Analytics without action said more in 32 words than most posts say in 320 words or most white papers say in 3200 words. (For those counting along, my opening sentence alone used 32 words). Godin’s blog post, in its entirety, stated: “Don’t measure