[ExI] [Bulk] Why so much published 'science' is wrong.
brent.allsop at canonizer.com
Sat Jul 11 20:47:29 UTC 2015
And don't forget Clifford Algebra. How many people have even heard of that?
You need that if you want to understand how brain representation can
harmonize in neurons.
Bad statistics aren't the only problem. Any and all of science
reporting, especially by religious organizations/people and the like.
Everything on the web is just more noisy bleating of the heard, often
leading us way astray. Minority experts can easily see through bad
scientific reporting, and the bleating herd. The only possible solution
is to have a system that can build and measure expert consensus, so the
herd can see through it, with the experts - everyone knowing the real
reasons, using good statistics or whatever, why. That which you can
measure, will improve. This is what is required to amplify the wisdom
of the crowd, knowing when bad hypothesis and beliefs have been
falsified. And the best way to know this, and what "scientific
evidence" is most responsible, is to measure how many experts jump
camps, because of it. There are "hard decisions", the minority experts
know we have to make, to get to the singularity in tact, as soon as
possible. We need to find some way so the entire heard can hear the
noise above the bleating noise of the herd, and change directions
faster, in a way that measures how many people are on board...
On 7/11/2015 10:16 AM, spike 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 similarly,
> 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 and
> 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?
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