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Oct 7 at 1:55 answer added civilstat timeline score: 3
Sep 27, 2020 at 6:26 history edited gung - Reinstate Monica
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Apr 13, 2018 at 11:43 comment added Philip Oakley The Nature paper (preprint) is also at arxiv.org/abs/1702.05178
Apr 13, 2018 at 9:31 comment added Philip Oakley @whuber, yes I have read that one. As some one who works in photonics, I suspect that it is part of the continued misrepresentation of the mathematical duality of "plane wave" vs "point particle" as being one sided. I strongly suspect that the 'randomness' is actually just unobservable quanta entering from behind the light cone. Most of the misrepresentation is because Gibbs used 4d Cartesian vector/matrix algebra rather than the Quaternion (Clifford) Algebra that Maxwell summarised his EM theory (art. 618 within his book)
Apr 12, 2018 at 13:30 comment added whuber @Philip Interestingly, at almost the same time you were writing that comment about randomness not existing, the NIST issued a press release claiming it does. An account appears in today's (4 April 2018) issue of Nature.
Apr 12, 2018 at 9:41 comment added Philip Oakley @whuber, Absolutely. One must think hard (and widely) about these things!! In my case I had hours of video, with hundreds of event, with long gaps between, so needed to reduce the data size of the non-event set for a simple logistic regression (each frame considered independently, little change between frames), so dropping lots of non-event frames was reasonable. The time sequence aspect was considered separately.
Apr 12, 2018 at 9:36 comment added Philip Oakley @Henry, Yep, that's a good example about the confusion about randomness and bias (is it chance of wining, or amount of winnings?). At some level, randomness doesn't exist xkcd.com/221 & Douglas Adams in The Hitchhiker's Guide to the Galaxy, “We demand rigidly defined areas of doubt and uncertainty.” ...
Apr 11, 2018 at 17:48 comment added whuber Systematic sampling, such as described by @Philip, often is analyzed as if it produced simple random samples, but it has pitfalls. For instance, if you were to measure a manufacturing process every day and sample every seventh measurement, you would be subject to confounding your results with a day-of-the-week effect, since (obviously) you would be sampling on the same day each week. You need to work harder to think of and address such subtleties when dealing with non-random samples.
Apr 11, 2018 at 14:25 comment added Henry @PhilipOakley: selecting balls 1,2,3,4,5,6 on the lottery gives you the same chance of winning as any other selection, but reduces your expected winnings as you are more likely to have to share the prize with others who had the same idea
Apr 11, 2018 at 14:13 answer added gung - Reinstate Monica timeline score: 6
S Apr 11, 2018 at 13:49 history suggested Peter Mortensen CC BY-SA 3.0
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Apr 11, 2018 at 13:22 review Suggested edits
S Apr 11, 2018 at 13:49
Apr 11, 2018 at 12:42 comment added Philip Oakley If the sampling technique introduces a bias, then it's not 'random'. If it does not introduce any bias then it is 'random' (for some definition of random;-). I've had sampling schemes that simply took every 7th sample to create a matched sample size to the counter sample. However I knew that there was no special aspect to that selection, so what may be thought of as a non-random sampling process was still effectively random. It's the same as selecting balls 1,2,3,4,5,6 on the lottery. It's just as random as any other sequence.
Apr 11, 2018 at 9:29 history tweeted twitter.com/StackStats/status/984000536277069831
Apr 11, 2018 at 4:16 answer added Michael Lew timeline score: 4
Apr 10, 2018 at 23:38 answer added Ben timeline score: 18
Apr 10, 2018 at 23:28 history asked Ágatha Isabelle CC BY-SA 3.0