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    Joined: Feb 2011
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    ... and in some fields, data-mining and informatics-oriented ones, he's simply incorrect about "math doesn't lead to discoveries."

    It most certainly can and does.

    I do agree with the second quote above, however, I would qualify that to posit that there is a lower limit. That floor should be statistics, and I've known far too many scientists in some of those softer disciplines who lacked that floor. It shows. Painfully.

    The problem with Wilson's assertion about "calling on" such experts when you need them is that, er-- you can't know what you don't know. Statistics is so integral to data reduction that one frequently cannot determine significance or even isolate correlations (which is where ideas and hypotheses COME from) successfully without it.

    So yeah. Sorry, but if your math skills prove inadequate to manage Gaussian statistics, STEM is (and IMO should be) pretty much closed to you. You're welcome to find a seat in the stands, though, or a different field of play. This simply does not apply to most people with average and up math aptitude, however. I've known people who have managed it even with below-average math skills, truth be told. Sheer force of will and devotion to science can accomplish a lot, even if it will never be effortless.





    Schrödinger's cat walks into a bar. And doesn't.
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    I was amused by the "For every ... there exists ... for which ..." bit. To say that, I'm pretty sure he also understands "For every epsilon, there exists delta, for which ..."

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    Make sure you distinguish between arithmetic and mathematics.

    DD11 detests arithmetic 'facts' and does not memorize. This is different from remembering random trivia she saw in a book once, which she does all the time. If she had never seen math outside of school she would think she was horrible at it and hated it. Instead we've supplemented all her life with conversations and books about mathematical ideas - try The Number Devil, it's interesting for adults and kindergarteners alike because the ideas are not the math you encounter in school - and she loves playing with math ideas and how they fit together, just like her science interests. (We haven't yet found a way to keep up with her scientifically.) At the moment we're just ignoring the arithmetic facts (lack of) speed and moving on to algebra as quickly as the school will let us.

    DH and I are both terrible at memorized facts. I did memorize in 5th grade but don't trust my memory; he calculates quickly to this day. I'm a scientist and he's an engineer.

    At Caltech, there is a rule that the youngest non-math major calculates the tip because the more mathematics you study, the worse your arithmetic gets. I think it's true. The one time I violated the rule we ended up with about a 45% tip.

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    I believe that the presence/absence of interest can muddy the picture considerably. However, speaking specifically of ability, there is probably at most a weak positive correlation between the two. DH is a scientist (bio-chem area) who was not particularly strong in math while I have an undergraduate math degree but physics was the only science area in which I had any talent. Of course ability is relative and we had to "excel" in both math and science at the high school level to be competitive for the top colleges to which we applied.

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    Originally Posted by HowlerKarma
    Sorry, but if your math skills prove inadequate to manage Gaussian statistics, STEM is (and IMO should be) pretty much closed to you.

    Totally fly-by post coming on my part here... no time to read all the links and replies, but just wanted to add, fwiw, yes, I agree that *understanding Gaussian statistics is important* (as well as within the reach of most people, whether or not they like math)... actually *computing* Gaussian statistics is done by calculators and computers and as a working scientist, I can tell you that it's the understanding of most math that counts once you're in the working world, not the ability to quickly spout out math "facts" smile

    FWIW, I do find it useful that I can quickly add/subtract/multiply etc - but I find that useful in the everyday world - at the grocery store, calculating a tip, etc. Being slow at those types of drill skills would not have limited me as a scientist at all.

    I'll also throw it out there - there are a few scientific fields where you really don't deal with statistics all that much either. And quite a few of the scientists I know who didn't study much math in college beyond dif-eq (because it wasn't needed for their field), did find later on that they needed some.. and they picked it up while they were working, usually through situation-specific instruction.

    No guarantees that any of that makes sense - as I said, I am reading and posting quickly at the moment!

    polarbear

    ps - for any parents who are worried about the age their kids became proficient at addition/subtract/mulitplication facts - fwiw, none of my kids picked them up quickly or at a young age. My EG ds13 didn't really have them down until 5th grade, and he's really *really* good at both science and math. My dd9 picked them up quickly than my other two, but that's because she went to a drill-and-kill school that practically sucked the love of math out of her (she's changing schools year, partly because of the constant repetition of math fact calculations over spending time learning actual, um, math). My dd11 did not pick them up quickly, still hesitates on some calculations, and quite honestly, is horribly slow to understand some of the basic math concepts also. But she's still a happy kid, and she also still loves science smile I see the largest hurdle for her, if she wants to pursue a career in science is getting into a good college science program as a freshman without having gone through advanced track math in high school as many of the other kids applying for admission will have. There *are* science fields that have people in them who will readily admit they don't like math and aren't good at it and there are science fields whose college curriculum doesn't include higher-level math beyond calculus and basic stats - I went through college (an all-STEM school) with quite a few of those folks in one particular field that I recall (our school had a limited number of study fields to choose from). I can see my math-hating dd enjoying and being successful in that field smile

    Best wishes,

    polarbear

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    DeHe Offline OP
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    Originally Posted by Bostonian
    Harvard biology professor E.O. Wilson (and inventor of sociobiology, making him one of my heroes smile ) has said in his new book "Letters to a Young Scientist" that some prospective scientists are needlessly deterred by doubts about their math skills.

    http://online.wsj.com/article/SB10001424127887323611604578398943650327184.html
    Great Scientist ≠ Good at Math
    E.O. Wilson shares a secret: Discoveries emerge from ideas, not number-crunching
    by E.O. Wilson
    April 5, 2013
    Wall Street Journal
    http://online.wsj.com/article/SB10001424127887323611604578398943650327184.html

    Quote
    For many young people who aspire to be scientists, the great bugbear is mathematics. Without advanced math, how can you do serious work in the sciences? Well, I have a professional secret to share: Many of the most successful scientists in the world today are mathematically no more than semiliterate.

    During my decades of teaching biology at Harvard, I watched sadly as bright undergraduates turned away from the possibility of a scientific career, fearing that, without strong math skills, they would fail. This mistaken assumption has deprived science of an immeasurable amount of sorely needed talent. It has created a hemorrhage of brain power we need to stanch.

    I speak as an authority on this subject because I myself am an extreme case. Having spent my precollege years in relatively poor Southern schools, I didn't take algebra until my freshman year at the University of Alabama. I finally got around to calculus as a 32-year-old tenured professor at Harvard, where I sat uncomfortably in classes with undergraduate students only a bit more than half my age. A couple of them were students in a course on evolutionary biology I was teaching. I swallowed my pride and learned calculus.

    I was never more than a C student while catching up, but I was reassured by the discovery that superior mathematical ability is similar to fluency in foreign languages. I might have become fluent with more effort and sessions talking with the natives, but being swept up with field and laboratory research, I advanced only by a small amount.

    Fortunately, exceptional mathematical fluency is required in only a few disciplines, such as particle physics, astrophysics and information theory. Far more important throughout the rest of science is the ability to form concepts, during which the researcher conjures images and processes by intuition.

    Everyone sometimes daydreams like a scientist. Ramped up and disciplined, fantasies are the fountainhead of all creative thinking. Newton dreamed, Darwin dreamed, you dream. The images evoked are at first vague. They may shift in form and fade in and out. They grow a bit firmer when sketched as diagrams on pads of paper, and they take on life as real examples are sought and found.

    Pioneers in science only rarely make discoveries by extracting ideas from pure mathematics. Most of the stereotypical photographs of scientists studying rows of equations on a blackboard are instructors explaining discoveries already made. Real progress comes in the field writing notes, at the office amid a litter of doodled paper, in the hallway struggling to explain something to a friend, or eating lunch alone. Eureka moments require hard work. And focus.

    Ideas in science emerge most readily when some part of the world is studied for its own sake. They follow from thorough, well-organized knowledge of all that is known or can be imagined of real entities and processes within that fragment of existence. When something new is encountered, the follow-up steps usually require mathematical and statistical methods to move the analysis forward. If that step proves too technically difficult for the person who made the discovery, a mathematician or statistician can be added as a collaborator.

    http://www.npr.org/2013/06/21/194230822/e-o-wilsons-advice-for-future-scientists
    E.O. Wilson's Advice for Future Scientists
    National Public Radio
    June 21, 2013

    Quote
    FLATOW: Thank you very, very much. This is almost like advice to the lovelorn sort of book, it's advice to would-be scientists. Why did you write this?

    WILSON: Well, 42 years of teaching at Harvard qualified me, and I had learned lot about what brings students into science, whether as professionals or as part of their general education program, and what drives them away. And I saw a lot of the brightest young people, the most qualified, potentially, to be in science and technology turned away because at an early stage in their career at Harvard they were just afraid of mathematics, and they were afraid of the kind of rigors that one experiences in the usual portrayal of scientists as white coat people standing at the blackboard explaining complex equations and other ideas to rapt audiences.

    FLATOW: Because you talk about your career and about your work with such passion in your book that I few people would know that a scientist could be as passionate and as successful about their work. And it seems like it's a necessary - or it's something like, almost like continuing to have a childlike curiosity about the world for your whole life.

    WILSON: Yeah, a passion, commitment to a subject, excitement over adventure, an entrepreneurial spirit. All these are more important than a very high IQ.

    FLATOW: And you say there that the Mensa-level people really don't make good scientists.

    WILSON: Well, I realize that this is one of the statements that has not proved controversial. Even my slight downplay of advanced mathematical fluency has not proved controversial. I've gotten a large number of responses on that, and almost - well, they're overwhelmingly favorable.

    But the one on - I call it optimum brightness. I present it as just a conjecture, but I got it from a principle that I gradually evolved knowing a lot of very successful scientists and from my own experience, the following principle. The ideal scientist is bright enough to see what needs to be done but not so bright he gets bored doing it. And I've discovered as time goes on that some of the most successful scientists in America, the most innovative, have IQs in the low 120s.

    And this began - this got me to start thinking about what happens to all these folks up in the 160, 170 IQ range that we hear about. So the conjecture says, well, it's too easy for them. And then that brings me then to the allusion you made to scientists - or that I've made - the ideal scientist thinks like a poet and works like a bookkeeper.

    It's the poet, the poetic aspects of science, that seldom get talked about. But I've always felt that scientists fantasize and dream and bring up metaphor and fantastic images as much as any poet, as anyone in the creative sciences - art, the creative arts.

    And the difference is that at some point, the scientist has to relate the dreams to the real world, and that's when you enter the bookkeeper's period. Unfortunately, it's the bookkeeper period which leads sometimes to months or years of hard work that too many prospective scientists and students interested in science see, rather than the creative period.

    Many people disagree with Wilson, and their responses can be found online.

    We actually listened to this interview because SciFry Fridays are a regular part of our week. DS HATED Wilson. Said he was totally wrong and started getting very agitated and then suddenly stopped and said, I am in Neil deGrasse Tyson's camp and find his theories more supportable. Whoa! Went from being 7 to being 30 in a minute and then asked me to turning off so we could listen to StarTalk.

    DeHe

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    NdGT is awesome.


    {ahem}




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