Here are the New York Times, CNN, and NBC. Here is Wikipedia for background.

The case has made several appearances on LessWrong; examples include:

- You Be the Jury: Survey on a Current Event (December 2009)
- The Amanda Knox Test: How an Hour Beats a Year in the Courtroom (December 2009)
- Amanda Knox: post mortem (October 2011)
- Amanda Knox Guilty Again (January 2014)

No. This was already discussed here.

If she had been randomly sampled from the general population then the prior probability would have been exceedingly small, but she wasn't randomly sampled, she was investigated because she lived with the victim. When someone is murdered, there is a high probability that the perpetrator is somebody in a close or frequent relationship with them.

Realistically, the prior probability of Knox being a perpetrator would be around 0.01, the same for Sollecito, with high positive correlation between them.

I disagree strongly. The fact that she lives with the victim doesn't shield off the effect of her demographic profile on the likelihood she committed the crime.

Let's analyze the problem using Bayes Net terminology. Let A={suspect=Knox's demographic profile}, B={suspect lives with victim} and C={suspect guilty}. Then your claim is that the net is structured as A->B->C, or that the demographic evidence is conditionally independent of guilt given co-habitation. My claim is that the net is structured as A->C<-B; both A and B affect the likelihood ... (read more)