Na, the lesson was a few paragraphs down
“More recently psychologists had challenged the universality of research done in the 1950s by pioneering social psychologist Solomon Asch. Asch had discovered that test subjects were often willing to make incorrect judgments on simple perception tests to conform with group pressure. When the test was performed across 17 societies, however, it turned out that group pressure had a range of influence. Americans were again at the far end of the scale, in this case showing the least tendency to conform to group belief.
Comment on Open thread weekend by Steven Mosher
Comment on Spinning the climate model – observation comparison by Brandon Shollenberger
Vaughan Pratt:
Each example would be a time series of length 140. Fit a trend line to each block of 10 points and observe whether the 14 trend lines alternate in slope. Run the program on a million such random examples and count how many alternate perfectly.
You want me to do a test with OLS calculations over ten points? That seems strange. I don’t even know what parameters I’d have to use to create that phenomena in such sparse data. Oh well. I guess I can do it.
The only way I can imagine getting more than 122 would be by careful tuning of the structure to bias it by making it prefer oscillations of period 20, which I think we would agree would not be in the spirit of this test.
I certainly don’t agree. The parameters I use are guaranteed to shape any periodicity I find. It’s like fitting a model. Why would I use random or bad parameter values rather than ones that give a good fit? If I did what you suggest, all it’d show is one noise structure can’t create the pattern you observe. It would say nothing about the multitude of other noise structures that could be used.
Anyway, I’ve built a (crude) function to test for periodicity like what you found. I’m currently just using the arima.sim function from r to generate my time series. Do you have specific parameters you think I should/should not use? I’d rather use a different approach for generating the series, but this can work as a starting point.
By the way, this examination isn’t just about increasing the odds. Unless I’m mistaken, some noise structures should make the pattern you found near-impossible to generate via noise. What would you say if I created a million series and none of them had the pattern you found?
(I need to improve my function’s efficiency before trying things with a million series. At the current rate, it would take half a day to test with that many. As I said, it’s a crude function.)
Comment on Spinning the climate model – observation comparison by Edim
Webby, I like your decription of me, but I’m not Italian – I’m Bosnian. Furthermore, I only take the oposing premise if that’s really my point of view. For example I agree with you that the annual cycle in atmospheric CO2 is caused by the annual SST cycle. We’re both contrarians regarding this matter.
Comment on Open thread weekend by Doug Cotton
Comment on Open thread weekend by Doug Cotton
Yes Don, burning bridges with Anthony is as easy as disagreeing with him.
Join the club!
Comment on Open thread weekend by Doug Cotton
Comment on Open thread weekend by Doug Cotton
Comment on Open thread weekend by tempterrain
Doug Cotton,
“But no, tempterrain, pressure does not maintain temperature.”
I think you must be confusing me with someone else. I didn’t say that.
so it’s Cotton and Loschmidt vs Martin, Boltzmann, and Maxwell eh?
I think you need to think again. Please don’t keep referring me to your “paper”. Its isn’t a paper. If you care to submit it to a proper Physics journal they’ll tell you where you’ve gone wrong. If I’m wrong in saying that and it does get accepted I’ll be the first to acknowledge it.
Comment on Open thread weekend by tempterrain
Yeah ‘they’ said it was cooling in the 60′s, then ‘they’ said they weren’t sure, then ‘they’ said it was warming later on.
But they never had a debate about it? They just switched opinions as directed by their political masters?
Comment on Spinning the climate model – observation comparison by Brandon Shollenberger
Quick update. I’ve greatly improved my code’s efficiency. If I’m willing to make one somewhat iffy choice, it can do a million series in about half an hour. That’s not too bad.
The iffy choice is using overlapping samples. Rather than create a million separate series, I create a single series long enough to have a million series within it, each beginning 10 points after the one before it.
By using overlapping segments, I decrease the amount of data used by more than 90%. I think it is fine because the series is stationary and the persistence in the data is far shorter than the segment lengths, but I’m not positive. I may be missing something, and that could affect interpretations of any results.
Comment on Open thread weekend by Doug Cotton
No physicist, including professors thereof, have proved me wrong on this, tempterrain. But it is easy to prove you wrong when you wrote ..
“Warm air does rise don’t forget. Conversely less energetic molecules fall and gain KE. So what ends up being equalised is KE rather than total energy and this means the column ends up being isothermal.”
This very clearly demonstrates to any physicist worth his salt that you don’t understand how maximum entropy evolves, as required by the Second Law of Thermodynamics. Nor do you understand how you should be applying certain limitations when using the ideal gas equation that you quote, also demonstrating your lack of understanding of the physics involved.
You can bury your head in the sand if you wish. But my paper is being subjected to the most extensive peer-review possible – namely world-wide open review. I challenge you to find a physicist who can successfully rebut it with a formal submission to Principia Scientific International, where two more professors have just signed up as members.
And, yes, my paper explains why Maxwell and Boltzman were wrong on this issue. I quote …
16. Conclusions
When Maxwell and Boltzmann dismissed Loschmidt’s postulate of a gravity gradient they did the world a great disservice, and they contributed to a belief in a non-existent warming by an imaginary
radiative greenhouse effect. The subsequent “calls to authority” should be a lesson for all in the scientific world, for this has resulted in an absolute travesty of physics. The greenhouse conjecture will inevitably take its brief place in history as the biggest and most costly mistake ever in the field of human scientific endeavour. Hopefully that will be soon.
Comment on Spinning the climate model – observation comparison by tonybclimatereason
Brandon
Good to hear you have refined your system. Not sure that using less data is an advance but you can try to convince me.
However the question must be asked as to how reliable the data is in the first place?
tonyb
Comment on Open thread weekend by Doug Cotton
Comment on Spinning the climate model – observation comparison by cd
I can’t believe that people actually debate this nonsense. There is a serious lack of proportion in these debates. You’re all talking about a few tenths of a degree.
The error in any estimate of global mean temperature is subject to great uncertainty. The sources of error/bias included in the choice of interpolation routines, projection methods never mind the likely errors in experimental setup, are very large. No one ever tries to run the same estimates using a range of techniques and a randomly sampled control population. Surely, good science starts with this – an attempt to determine sensitivity to all the aforementioned sources of error.
Even when they use a technique such as BEST did (i.e. Kriging) that gives an estimate of confidence at each girdded temperature value they don’t even use/report these estimates.
Comment on Spinning the climate model – observation comparison by Vaughan Pratt
Comment on Spinning the climate model – observation comparison by cd
These people think way too much on the wrong thing.
No one is doing the science. I’ll repeat:
The error in any estimate of global mean temperature is subject to great uncertainty. The sources of error/bias included in the choice of interpolation routines, projection methods never mind the likely errors in experimental setup, are very large. No one ever tries to run the same estimates using a range of techniques and a randomly sampled control population.
I think the problem in this field is that the application of statistical methodologies and climate modelling is carried out by people who don’t fully understand the methods they are using. There is very often a disconnect between the people that actually develop the methods and write the code and those that use them. Hence all this arguing over attribution based on historical records of a “spatial statistic” derived from methods that introduce their own bias. Then there are the issues surrounding experimental error.
Comment on Spinning the climate model – observation comparison by WebHubTelescope
Simple is good.
Like Tomas,
I could have written a comment on the analytic intractability of the three-body problem, but that does not advance the yardstick.
Sad state of affairs when the nominees for best science blog go to places such as WUWT, where the stories revolve around how many women Willis Eschenbach has simultaneously infected. Willis is able to solve the 3-body problem, if you know what I mean, nudge, nudge
Seriously, this is the state of the skeptical rership. I am not part of the problem. Get yourself a mirror.
It is all FUD as far as I am concerned
, and this is just a soap opera to me.
Comment on Open thread weekend by kim
Heh, Cap’n, imagine trying to teach him to fish.
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Comment on Lindzen et al.: response and parry by ancient mosaics
Your site doesn’t show up properly on my iphone – you may want to try and fix that
Comment on Open thread weekend by Bad Andrew
I think ol’ Joshua gets paid by the non-answer.
Andrew