[ExI] [Bulk] Why so much published 'science' is wrong.
William Flynn Wallace
foozler83 at gmail.com
Sat Jul 11 17:35:32 UTC 2015
Statistical significance has nothing to do with actual significance,
though. A statistically significant effect can be trivially small. Or even
Yes, especially if you run the N up way high, but an effect that has real
world significance will have statistical significance as well. bill w
On Sat, Jul 11, 2015 at 11:16 AM, spike <spike66 at att.net> wrote:
> >... On Behalf Of spike
> Subject: Re: [ExI] [Bulk] Why so much published 'science' is wrong.
> >... On Behalf Of BillK
> >>...Statistical significance has nothing to do with actual significance,
> though. A statistically significant effect can be trivially small. Or even
> completely illusory.
> >>...I've got a feeling that this is especially relevant to ESP research,
> where much of the claimed effect might probably be just statistical
> creations. BillK
> >...BillK...Even with sharp students at their prime, I fear we would be
> appalled at how many draw the wrong conclusions...spike
> BillK's comment has me thinking about a topic we discussed here a few years
> ago. A proposal was made at an education conference (don't know when or
> where, would like to know) where the presenter proposed a revamping of
> standard engineering education. Currently the standard curriculum requires
> four quarters of calculus, then differential equations, and a couple
> (sometimes three (and five electives will get you a second major in math))
> quarters of more advanced math electives such as multivariate calculus of
> variation, complex variables, matrix algebra, all that kind of cool stuff.
> In all that, there is only one quarter of statistics required for most
> engineering bachelor's degrees, with a second quarter usually offered as an
> Someone at an engineering education conference proposed replacing the
> calculus series with a statistics series: make it one quarter of calculus
> where you get right to the point, explain what the integral and the
> differential functions do and forget teaching the mainstream students all
> those now nearly useless integration techniques. Show them how to use
> Wolfram's magic trick on the computer, how to do implicit integration and
> hit the high points, how to set up a spreadsheet or Matlab routine to do
> numerical integration, then don't worry about all those integration
> techniques which are never used in the real world but eat up a lot of
> classroom time. Then use those three (or four in some cases) quarters to
> teach the right ways to use statistics.
> I was horrified when I first heard it. Engineering students have been
> required to master calculus since about a week after Newton and Leibniz
> discovered it. The methods as taught haven't changed much at all in the
> last couple hundred years. This would be a major change.
> But the idea started growing on me immediately. As I heard it, the
> engineering education conference at which it was proposed reacted
> with plenty of the attendees thinking it is a grand idea. I think I have
> joined that camp: reduce the calculus, pound on the statistics. The USA
> Britain educate a big fraction of the world's engineers and scientists, so
> we really need to get this right. Explain to the students the right way to
> use the concept of a null hypothesis. Don't worry about it if they can't
> integrate or differentiate, but don't give away any science or engineering
> degrees to anyone who doesn't understand the concept of statistical
> Anyone here up to speed on that proposal?
> extropy-chat mailing list
> extropy-chat at lists.extropy.org
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