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the log-log[1] "Posts vs Sats Stacked" [2nd row, left side] shows it beautifully

  1. linked in case people like wikipedia; tl;dr, switching both scales of a graph from linear to logarithmic causes some kinds of data behavior to "jump out" because the log scales turn certain kinds of curves into lines of recognizeable angles

I'm being facetious, cuz all the power-law log-log stuff is complete bullshit (#1433264).

Nice to find a Pareto distr in the SN wilderness

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40 sats \ 0 replies \ @adlai 8h

honestly I'm not well-versed in the detailed differences.

the line on the log-log chart, with meta outlying, is undeniable.

I'm being facetious, cuz all the power-law log-log stuff is complete[1] bullshit (#1433264).

I agree that quibbling over whether some fitted curve is n^x, x^n, or something else, is futile in most situations... although a conversation in one situation could be complete bullshit, without reducing the abstract accuracy of the mathematics.

  1. emphasis mine, on the word that pissed me off ...

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I thought Pareto distributions show up everywhere

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1 sat \ 0 replies \ @adlai 1h

unless you[2] metrize[3] by something absolute, then the distribution of distributions remains hopelessly subjective[1]

  1. i.e., whichever question interests anyone, will reveal more about where specifically data were collected, and how, rather than about isotropic properties of the data-space

  2. "you" could be part of the data-space, although obviously it's easier to remove bias if the study designer isn't navel-gazing

  3. the "default metric" in this case would just be radial density, looking out from one subjective point, into the surrounding data-space; ideally, averaging that across multiple points; theoretically, one could hope to move beyond this limited frequentist cloud, although I haven't encountered anything to suggest humanity has done this yet.

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Yahyah, a little bit

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