This article, or at least the portion posted above, is a perfect example of why everyone should go through at least one class of advanced statistics and one class in critical/logical thinking.

First of all, in any similar statistical analysis where you're trying to find a group with a certain characteristic, your main population that you're pulling from (let's use security screening as an example) is one and the same. What this means is that, for arguments sake, we're talking about 50 million flyers per year (with a huge % of this group flying more than once per year).

Now, while all the 50MM get profiled in the system (go through security), only a portion get flagged by the system for security purposes (secondary screening). Let's assume 1 million (again my number) get pulled for secondary due to profiles that have even the slightest connection as a potential terrorist, possible Visa issues, country of origin, cash tickets, yada, yada, yada.

Out of this million, the system would find X who are future terrorists, in his case 990 people, while missing 10. On the flip side, his assumption of a "Type B" mistake yields almost 10,000 false readings. I have no idea where his leap to an arrest for each false reading came out, and when you use actual numbers for your screened population, the rations are completely different than what the article states.

It's completely unprofessional to publish this type of BS in a paper under the guise of a scientific analysis.