Does this defense lawyer's probability argument sound like BS?

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Discussion Overview

The discussion centers around the application of probability and Bayes' theorem in a defense lawyer's argument regarding a legal case. Participants explore the validity of the probability calculations presented, particularly in the context of establishing guilt and interpreting likelihood ratios. The conversation touches on theoretical and practical implications of these concepts in legal scenarios.

Discussion Character

  • Debate/contested
  • Mathematical reasoning
  • Conceptual clarification

Main Points Raised

  • Some participants express skepticism about the author's understanding of probability, suggesting they may be a "pop scientist."
  • Others argue that the application of Bayes' theorem seems reasonable but highlight challenges in establishing prior probabilities and interpreting results.
  • A participant raises concerns about the initial assumption of guilt being set at 1/200,000, arguing that it does not account for the suspect's known history as a sex offender, which may skew the probability assessment.
  • There is a discussion about the interpretation of likelihood ratios, with some participants questioning whether it is appropriate to treat them as probabilities and noting that likelihood ratios represent the strength of evidence rather than direct probabilities.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the validity of the probability argument. There are multiple competing views regarding the assumptions made in the calculations and the interpretation of likelihood ratios.

Contextual Notes

Participants note limitations in understanding probability among the general public, as well as the specific context of the suspect's background affecting the assumptions made in the probability calculations.

swampwiz
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Either that, or the author is a typical "pop scientist" author that doesn't understand probability too well.

https://nautil.us/issue/4/the-unlikely/the-odds-of-innocence
 
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swampwiz said:
Either that, or the author is a typical "pop scientist" author that doesn't understand probability too well.

https://nautil.us/issue/4/the-unlikely/the-odds-of-innocence
What's wrong with it? This seems like an ok application of Bayes theorem.
The main problems with this kind of calculation are the difficulty of establishing the prior probability that someone is guilty, and the interpretation of the result. (What percentage was reasonable doubt again, your honour?)
 
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The general point seems sound to me, but I'd have a couple of objections;
1. General: most people don't have a good enough understanding of probability to properly evaluate the arguments.
2. Specific: I'm not happy with the initial assumption of guilt of 1/200000. That seems to assume he was randomly selected from the local population to be put on trial, or at least to have his DNA tested, but that isn't the case. He was a known sex offender, and therefore likely to be of interest as a suspect, and his DNA was already on the database and found to be a match. He was not a random choice.
 
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I would have to think about the defence's likelihood ratio argument. I have never seen a likelihood ratio interpreted as a probability. I think that may be an error. Or it may be using the term "likelihood" in a different context than I am used to.
 
mjc123 said:
Specific: I'm not happy with the initial assumption of guilt of 1/200000. That seems to assume he was randomly selected from the local population to be put on trial, or at least to have his DNA tested, but that isn't the case. He was a known sex offender, and therefore likely to be of interest as a suspect, and his DNA was already on the database and found to be a match. He was not a random choice.
I think that is a good point. Probably the beat approach would have been to start with the “random male” number but add “convicted sex offender” as an additional explicit piece of evidence.
 
FactChecker said:
I would have to think about the defence's likelihood ratio argument. I have never seen a likelihood ratio interpreted as a probability. I think that may be an error. Or it may be using the term "likelihood" in a different context than I am used to.
The likelihood ratio isn’t a probability because it can be greater than 1. It is the strength of the evidence. If you multiply the prior odds by the likelihood ratio then you get the posterior odds.
 
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