« R 2.10.1 released | Main | R Site Search with the 'sos' Package »

December 14, 2009

Comments

Feed You can follow this conversation by subscribing to the comment feed for this post.

Uh, that IS Bayes' Theorem.

You're right of course, but presenting it as conditional probability (or even probability within subsets) makes in more approachable than quoting Bayes' Theorem.

I like it.

The article is basically explaining the commonly misunderstood difference between sensitivity and positive predictive value. Obviously, people fail to understand the impact of what you are conditioning on. I've email a link to my biostat class, since we spent some time on this.

This will be the case as soon as the number of positives in the population (the 0.5%) is small. Exactly the same argumentation applies when you are "testing" for terror suspects through data mining/random searches/etc -- your system becomes ineffective as it is flooded by false positives.

The comments to this entry are closed.

Search Revolutions Blog




Got comments or suggestions for the blog editor?
Email David Smith.
Follow revodavid on Twitter Follow David on Twitter: @revodavid
Get this blog via email with Blogtrottr