Can Mathematical Certainty be Achieved for Common Claims?

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Discussion Overview

The discussion centers on the possibility of achieving mathematical certainty regarding the truth of common claims based on witness testimony and lie detector results. Participants explore the implications of statistical analysis in legal contexts, the nature of evidence, and the limitations of mathematical proofs in this scenario.

Discussion Character

  • Debate/contested
  • Mathematical reasoning
  • Conceptual clarification

Main Points Raised

  • One participant questions whether mathematical certainty can be established from lie detector results, suggesting that statistical methods do not yield definitive proof about the occurrence of events.
  • Another participant emphasizes that the best outcome from such tests may only indicate a belief among witnesses rather than objective truth.
  • Concerns are raised about the interpretation of results in legal contexts, with one participant noting that while evidence may be sufficient for legal standards, it does not equate to mathematical proof.
  • A later reply suggests that while statistical methods can provide insights, they cannot guarantee certainty for individual cases, highlighting the complexities involved in applying population statistics to unique witnesses.
  • Participants discuss the need for clear definitions of terms like "scientific evidence" and "perfect questions," indicating that ambiguity in language can lead to misunderstandings in the argument.
  • One participant proposes a hypothetical scenario involving an ideal lie detector to explore the potential for anecdotal evidence to be interpreted as scientific evidence, prompting further questions about the validity of such interpretations.

Areas of Agreement / Disagreement

Participants express conflicting views on the relationship between statistical evidence and mathematical certainty. There is no consensus on whether lie detector results can provide definitive proof of truth regarding common claims.

Contextual Notes

Participants note the limitations of statistical methods in individual cases, the influence of various factors on witness reliability, and the challenges of defining key terms in the discussion.

Ivan Seeking
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Assuming that the most sophisticated lie detectors can yield results with a known degree of accuracy given a large enough sample, is it possible to state with any mathematical certainty whether or not a common claim is true or false, given a large enough sample of alleged witnesses. Assume that we have a clearly identified type of event, but not the same event common to all alleged witnesses.

For example, if 1000 people all claim to have seen a automobile accident at close range [described as absolute certainty] - again, not the same accident, but an accident - and if we can say that our lie detector yields results accurate to 90% in 75% of the people in any large sample, with the other 25% being completely unreliable, and if 900 of the 1000 alleged witnesses pass the lie detector test as truthful, do we have a mathematical statement of certainty as to whether or not automobile accidents happen?
 
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The short answer is no. The longer answer is "that isn't how statistics work", and there's an even longer answer abuot what you're doing isn't maths, and all you're doing is proving something in a model of something, though what the thing you are proving is, and what the model is of are hazy.
 
Ack, the C-word!


All other issues aside, the best result you could get is that there is a segment of the population that believes they've seen a car accident at close range.
 
In a court case, that may be sufficiently rigorous as evidence. Brain fingerprinting also works on somewhat the same basis.
 
I seem to be getting conflicting answers. I realize that the interpretation of events "believed" by the claimants is what's really tested. I was allowing for absolute certainty with the understanding that this is really a subjective term. However, from what Hurkyl said, we could get a result indicative of truth?
 
Ok, let me put it this way:

you've produced an argument that proves something in the larger sense of the word proved, proved in legal terms, provided evidence that it is more than reasonable to believe. That argument involves mathematics. But it is not, in my opinion, something that would be called a "mathematical proof" in the sense that a mathematician may use the phrase - it proves nothing about or in mathematics, and arguable not in any mathematical model of something, at least not of the thing you seem to be claiming. We may arguablu have shown mathematically, that some people think they have seen something that they consider to be an accident.
 
Okay thanks; I see your point. This was a poor choice of words on my part.
 
Okay one more question...getting to the heart of things [watch Hurkyl gasp and fall over dead! :biggrin:]

Since we are so found of ideal [perfect] devices in physics, let's assume for a moment that we have lie detector test that uses perfect questions! :smile: In principle, could a well designed test of claim X as described be used to interpret anecdotal evidence for X, as scientific evidence for X?
 
please define your terms: what is scientific evidence; what is a perfect question; anecdotal evidence...?

Maths is essentially about definitions. If we know what you mean we can sau, if we don't we're having a semantic argument about things we do not agree upon.
 
  • #10
Please use your own defintions.
 
  • #11
:smile: Good research is like finding a sequece or function that has a limit; but not, yeah know?

"A Mathematician is a machine for turning coffee into theorems." -Erdös, Paul Nov. 1992
 
  • #12
Sure you can do it statistically - but not for an individual

There are two questions you can try to answer:
1. Is the lie detector better than a coin?
2. What is the probability for
a) a person with a positive test result to have actually lied
b) a person with a negative test result to have actually told the truth.
Question 1 can be dealt with with a Fisher 2x2 contingency table test and it is rather straight forward.
If you want more detail, you will find that there is some threshold involved in interpreting the lie detector test, e.g. some minimal increase of skin conductivity to diagnose a lie. In addition there is a proportion of liars in your population.
Both variables enter in the probabilities 2a and 2b and one should be fine tuned to the other bearing in mind the cost of wrong decisions one way or the other.

The basic problem for application in a trial is to find a population for which the witness is a representative, because the single witness is unique and has not been found according to some definite inclusion/exclusion criteria. The individual comes with a certain stress resistance, a social background, childhood experiences, vegetative stability etc. All of these are covariates that would have to be tested before one can apply the population statistics to the single individual. No soap. Any decent lawyer/statistician team could tear such a result to pieces, imho - well unless the poor guy is in Guantanamo. But then you are into the virtual reality business anyway.
Remember, the price for lying is that you start to believe your own lies and then no lie detector can help you.
 
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