Skepticism

Skepchick Quickies 9.15

Amanda

Amanda works in healthcare, is a loudmouthed feminist, and proud supporter of the Oxford comma.

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15 Comments

  1. Kevin Trudeau says he can’t pay his FTC fines

    He should get my new book:
    “Secret Ways to Obey The Law That They Don’t Want You to Know”

  2. Can someone please explain to me the generic plurals story? I’ve read the last four paragraphs a bunch of times but I’m not getting it.

  3. I would think a simple financial investigation demonstrate whether or not Trudeau’s claims of poverty are true. And if not, couldn’t he 1) still be liable for the fine and 2) be charged with fraud…again…for lying about not being able to pay?

  4. @CJ.Sevilla:

    The meat of the nut is half-way through the blog post:
    “I propose a voluntary ban on the use of generic plurals to express statistical differences, especially in talking to the general public about scientific results in areas with public policy implications.”

    and

    “This would lead us to avoid statements like “men are happier than women”, or “boys don’t respond to sounds as rapidly as do girls”, or “Asians have a more collectivist mentality than Europeans do” — or “the brains of violent criminals are physically and functionally different from the rest of us”. At least, we should avoid this way of talking about the results of scientific investigations.”

  5. “Why are so many celebrities angry right now”

    LOL Or maybe it’s because they are drunk and/or fucked up on drugs? Like Kanye? Man it was obvious he was trashed.

  6. Everyone needs to run out and do some jumping jacks. That’s exercise. Exercise releases endorphins. Endorphins make you happy, and happy people don’t blow up all over the place!

  7. @CJ.Sevilla: I’m not sure what precisely it is you don’t understand about it, but it is pretty difficult stuff to grasp. Like numbers are difficult to grasp for a culture that doesn’t have them. In other words, as long as the media keeps hijacking the results of scientific studies and turning them into sensationalist pieces by oversimplifying their actual meaning into alarmist crap like “doing such-and-such increases your chances of dying of this-or-that by 50%” the general public is going to lap it all up because they don’t understand what that actually means due to a lack of understanding even basic statistics.

    FWIW, I don’t pretend to understand it all either, but some basic statistics in school combined with hanging out on skeptic forums and blogs the last 7 years, has erradicated the worst misconceptions.

  8. Shouldn’t Mercury be doing something useful, like running errands for the Gods, or causing autism, or something? And, where is Retrograde anyway? Jugoslavia?

  9. And yet, we can distinguish anglerfish from other fish and flies from other insects. (First comment under post, S.J. Gould quote.) Clearly, there are sets of features that group anglerfish and flies.

  10. @CJ.Sevilla:

    The following is one of the comments from the article that sums it up nicely:

    J. W. Brewer said,

    September 14, 2009 @ 11:44 am

    Actually, perhaps because they typically have considerable independent knowledge of the relevant underlying data, I would think that very few people think the statement “Men are taller than women” means the shortest man is taller than the tallest woman and/or that pointing to a particular 5′2″ man or 6′2″ woman makes the statement untrue. If you showed them a graph with overlapping bell curves of the male and female height distributions in a given population with a fairly simple explanation, many would probably get it and say “yeah, that’s pretty much what I meant by ‘Men are taller than women.'” The question is then whether they will systematically misinterpret other statements in the same syntactic form where they don’t have a good prior sense of what the data likely looks like, perhaps by implicitly assuming a larger distance between the peaks of the respective bell curves than the data, if graphed, would show. (If the problem with the study is that the sample size is too small or poorly selected to scale up reliably to the group it’s supposed to represent, that seems like a separate scientific/journalistic integrity issue than how to describe overlapping bell curves with a difference between means that is deemed statistically significant but much less than 1 SD.)

    But maybe there are other syntactically identical statements that due to context and the listener’s prior knowledge of the world are interpreted differently. Take “men can run faster than women.” Is this more likely to be understood as a claim about means or as a claim about the rightward tails, i.e. that at any given level of track competition from a county high school championship to the Olympics the winning female runner in any given event will usually post a time slower than the winning male runner and often a time slower than the slowest male runner who qualified for the male-only finals? And really, is there any obvious non-essentialist justification for segregating athletic competitions by sex (“women’s sports are a waste of time” could just mean “integrate now and may the fastest runner regardless of sex win”)? I certainly don’t object to the practice myself, but I’m not on an anti-essentialist crusade.

  11. @Glow-Orb:
    From J. W. Brewer’s statement:
    The question is then whether they will systematically misinterpret other statements in the same syntactic form where they don’t have a good prior sense of what the data likely looks like, perhaps by implicitly assuming a larger distance between the peaks of the respective bell curves than the data, if graphed, would show.

    I think that is exactly the problem.
    With “men are faster than women”, there is probably an implicit feeling that in 90% of the cases, a man is going to run faster than a woman, while that number is probably much lower, with a much bigger overlap. And what to make of statements like “thin people are faster than fat people”? Without seeing the data graphed, I would assume quite a small overlap, but is that really true?

    This is the essence of the article. We’re using simple words to describe complex datasets. Like using simple unquantified words such as many and few to describe values like 12 and 3. Important information is lost in the transition, distorting the whole story.

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