4 ms·

having a history of cheating in a game that is mostly otherwise honor bound is a very very very bad sign. Don't be fooled by the "when he was younger" bit. Ever

by ouid 4y ago

having a history of cheating in a game that is mostly otherwise honor bound is a very very very bad sign. Don't be fooled by the "when he was younger" bit. Everything that you did you did when you were younger, it has been less time since hans was last caught cheating than the interval between that time and the previous one. Don't let the statisticians convince you that they know what they're doing either. Statistics, as a discipline, is essentially predicated on the principle that the objects of study do not know that they are being observed. Without this assumption, the domain is now more accurately described as game theory. Statisticians will happily and confidently ignore this and draw very wrong conclusions as a result.

Maursault 4y ago
> Statistics, as a discipline, is essentially predicated on the principle that the objects of study do not know that they are being observed. There is no such "principle" in statistics. Statistics is based on statistical methodology, i.e. formulas, models, and techniques that are used in statistical analysis of raw research data, which is collected, organized, analyzed, interpreted and presented. The Hawthorne effect, "a type of reactivity in which individuals modify an aspect of their behavior in response to their awareness of being observed,"[1] arose from analysis of a statistical study. > Without this assumption, the domain is now more accurately described as game theory. Game theory is utilized for decision-making in strategic environments where rational agents interact with each other. Statistics, on the other hand, is employed for reasoning in non-adversarial settings where the samples are assumed to be generated by some stationary and non-reactive source. > Statisticians will happily and confidently ignore this and draw very wrong conclusions as a result. Contradiction. You've already claimed that statistics is "essentially predicated on the principle that the objects of study do not know that they are being observed." Yet now you're claiming experts "confidently" ignore their discipline's "essentially predicated" principle. [1] https://en.wikipedia.org/wiki/Hawthorne_effect https://en.wikipedia.org/wiki/Hawthorne_effect
- ouid 4y ago
  There is a difference between a subject that changes with observation and a subject that changes adversarially with your statistical methods. A qualitative difference.
  - roflyear 4y ago
  - Maursault 4y ago
    Statistical methods may include observation during the gathering of data. Whether or not change is measurably different from adversarial change depends on the variables chosen. It is clear that two distinct disciplines can approach the same problem with varying results without invalidating the entire other discipline. There is a difference between sound argument and a straw man employing equivocation. A qualitative difference.
    - ouid 4y ago
      Sorry for the late reply, I had to collect my thoughts a bit and I'm quite busy. First, I have not invalidated the discipline, I have said not to trust statisticians who are clearly acting outside the bounds of the fundamental assumptions of statistics, and that statistical methods DO NOT function on adversaries. Consider the following two scenarios: 1) Alice and Bob are sending messages to each other in a lanugage I don't understand, and I, using statistical methods, wish to find out what they are saying. 2) Alice and Bob are sending messages to each other and don't want me to gain any information about this messages. I, using statistical methods, wish to find out what they are saying. In scenario 1, I am likely to succeed. In scenario 2, the consensus is that I'm fucked. In just about every way. I can't tell what they're saying, I can't tell that any message that I have discerned is meant to mislead me, or doesn't carry some additional message hidden in the entropy of the message that was meant to mislead me. I can't tell if the communication is just noise meant to distract me, and if we want to talk practically, I can't even tell if they can communicate. Basically the only inference that I can draw is that they can't communicate faster than the speed of light. Here's another example: Gerrymandering. The scenario is that one party has a clear advantage in terms of number of representatives vs proportion of population. We must establish whether that number was arrived at fairly, or by cheating. We assume that the party in charge of drawing the borders knows what tests we can perform, because that is always the assumption that you give to an adversary. The adversary has a very simple (though potentially computationally expensive) algorithm to run. Check all possible border configurations for both advantage and your cheat detection. Pick the one which maximizes advantage which does not pass the cheat threshold, or just whatever your utility is. Statistics needs the assumption of good faith in order to operate. Anyone who uses statistical methods when that assumption that cannot be made is at best a bad statistician.

by ouid 4y ago

Maursault 4y ago

> Statistics, as a discipline, is essentially predicated on the principle that the objects of study do not know that they are being observed. There is no such "principle" in statistics. Statistics is based on statistical methodology, i.e. formulas, models, and techniques that are used in statistical analysis of raw research data, which is collected, organized, analyzed, interpreted and presented. The Hawthorne effect, "a type of reactivity in which individuals modify an aspect of their behavior in response to their awareness of being observed,"[1] arose from analysis of a statistical study. > Without this assumption, the domain is now more accurately described as game theory. Game theory is utilized for decision-making in strategic environments where rational agents interact with each other. Statistics, on the other hand, is employed for reasoning in non-adversarial settings where the samples are assumed to be generated by some stationary and non-reactive source. > Statisticians will happily and confidently ignore this and draw very wrong conclusions as a result. Contradiction. You've already claimed that statistics is "essentially predicated on the principle that the objects of study do not know that they are being observed." Yet now you're claiming experts "confidently" ignore their discipline's "essentially predicated" principle. [1] https://en.wikipedia.org/wiki/Hawthorne_effect https://en.wikipedia.org/wiki/Hawthorne_effect

ouid 4y ago
There is a difference between a subject that changes with observation and a subject that changes adversarially with your statistical methods. A qualitative difference.
- roflyear 4y ago
- Maursault 4y ago
  Statistical methods may include observation during the gathering of data. Whether or not change is measurably different from adversarial change depends on the variables chosen. It is clear that two distinct disciplines can approach the same problem with varying results without invalidating the entire other discipline. There is a difference between sound argument and a straw man employing equivocation. A qualitative difference.
  - ouid 4y ago
    Sorry for the late reply, I had to collect my thoughts a bit and I'm quite busy. First, I have not invalidated the discipline, I have said not to trust statisticians who are clearly acting outside the bounds of the fundamental assumptions of statistics, and that statistical methods DO NOT function on adversaries. Consider the following two scenarios: 1) Alice and Bob are sending messages to each other in a lanugage I don't understand, and I, using statistical methods, wish to find out what they are saying. 2) Alice and Bob are sending messages to each other and don't want me to gain any information about this messages. I, using statistical methods, wish to find out what they are saying. In scenario 1, I am likely to succeed. In scenario 2, the consensus is that I'm fucked. In just about every way. I can't tell what they're saying, I can't tell that any message that I have discerned is meant to mislead me, or doesn't carry some additional message hidden in the entropy of the message that was meant to mislead me. I can't tell if the communication is just noise meant to distract me, and if we want to talk practically, I can't even tell if they can communicate. Basically the only inference that I can draw is that they can't communicate faster than the speed of light. Here's another example: Gerrymandering. The scenario is that one party has a clear advantage in terms of number of representatives vs proportion of population. We must establish whether that number was arrived at fairly, or by cheating. We assume that the party in charge of drawing the borders knows what tests we can perform, because that is always the assumption that you give to an adversary. The adversary has a very simple (though potentially computationally expensive) algorithm to run. Check all possible border configurations for both advantage and your cheat detection. Pick the one which maximizes advantage which does not pass the cheat threshold, or just whatever your utility is. Statistics needs the assumption of good faith in order to operate. Anyone who uses statistical methods when that assumption that cannot be made is at best a bad statistician.