Daniel_Burfoot comments on [LINK] Amanda Knox exonerated - Less Wrong Discussion
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Comments (58)
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 of guilt, and in particular A substantially reduces the likelihood of guilt as James_Miller points out (Note that I'm not saying B is irrelevant, obviously this is wrong).
I am very confident in this claim and would wager long odds in favor of it.
No.
I agree.