You realize we’re talking about a hypothetical scenario where one person in the lineup is a worm farmer, right? I guess you don’t want to acknowledge that because it would mean admitting that you’ve been terribly wrong this whole time. I can’t wait for your next reply where you write 10 paragraphs about how worms aren’t real therefore the whole premise is wrong and you’re right.
I honestly find this person’s compulsion to never admit they’re wrong to be mildly fascinating. They just keep digging and creating the most outlandish reasons for why they think everyone else is wrong including the very person who asked the question to begin with.
No, the point is that one of them is actually the suspect lmfao. And guess what, if it’s not, they tell you ahead of time. You’re just wrong on every level here, and are just making yourself look foolish now.
The suspect, along with several “fillers” or “foils”—people of similar height, build, and complexion who may be prisoners, actors, police officers, or volunteers—stand side-by-side, both facing and in profile. There is crucial information that should be conveyed to the eyewitness prior to viewing the lineup. It is necessary to inform the eyewitness that it is possible the perpetrator is not present in the lineup.[1]
Because you dont actually understand what random is.
I didnt bring up police line ups that’s someone else in this thread. Im just happy to point out how those are essentially random selection as well.
My original point was that the OP was ambiguous on the selection process used for the population. thusly assuming a random selection process from the overall popullation is just as valid as assuming 1 worm farmer + 9 randoms.
Now: randomness.
Given a random population of N entities, assume you want a sample of M where M < N and you decide to filter by Y to get X sample.
X is still random despite the filtering. all you’ve done is biased the N random population towards Y. but unless you remove the initial randomness (somehow… which is almost impossible btw). this is why so much of science is predicated on collecting large datasets because we have to make sure enough of the data has the attributes we want that it’ll show up for study once we apply our faulty filtering mechanisms. and its why we spend so much effort creating better and better filters. its also why algorithm that leverage randomness are so powerful, because they match the reality of the problems being solved.
Using the line up as an example:
witness says the individual they saw had a long wide nose and a blue shirt.
reality: The detective has very different definition of what a wide/long nose is than the witness.
applying those two faulty filters to population N is still going to result in a random population because the initial candidate selection before applying those two (faulty) filters is random.
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😂
You realize we’re talking about a hypothetical scenario where one person in the lineup is a worm farmer, right? I guess you don’t want to acknowledge that because it would mean admitting that you’ve been terribly wrong this whole time. I can’t wait for your next reply where you write 10 paragraphs about how worms aren’t real therefore the whole premise is wrong and you’re right.
feel free to re-read the thread as many times as it takes for you to understand where you fucked up. =)
They fucked up by responding to you.
I honestly find this person’s compulsion to never admit they’re wrong to be mildly fascinating. They just keep digging and creating the most outlandish reasons for why they think everyone else is wrong including the very person who asked the question to begin with.
No, the point is that one of them is actually the suspect lmfao. And guess what, if it’s not, they tell you ahead of time. You’re just wrong on every level here, and are just making yourself look foolish now.
You just aren’t all there are you?
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Because you dont actually understand what random is.
I didnt bring up police line ups that’s someone else in this thread. Im just happy to point out how those are essentially random selection as well.
My original point was that the OP was ambiguous on the selection process used for the population. thusly assuming a random selection process from the overall popullation is just as valid as assuming 1 worm farmer + 9 randoms.
Now: randomness.
Given a random population of N entities, assume you want a sample of M where M < N and you decide to filter by Y to get X sample.
X is still random despite the filtering. all you’ve done is biased the N random population towards Y. but unless you remove the initial randomness (somehow… which is almost impossible btw). this is why so much of science is predicated on collecting large datasets because we have to make sure enough of the data has the attributes we want that it’ll show up for study once we apply our faulty filtering mechanisms. and its why we spend so much effort creating better and better filters. its also why algorithm that leverage randomness are so powerful, because they match the reality of the problems being solved.
Using the line up as an example:
applying those two faulty filters to population N is still going to result in a random population because the initial candidate selection before applying those two (faulty) filters is random.
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no, i havent. and in fact anyone asserting this is absolutely moronic and has no idea what they are talking about for reasons I’ve already mentioned.
im not doubling down you dunces just dont know what you’re talking about. again as I’ve stated repeatedly.
lets start over so you can understand:
you have:
you are asked:
facts:
chucklefucks:
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