Discussion in 'Contrails and Chemtrails' started by Mick West, Jun 22, 2015.
Yeah, It's still ongoing though. Don't want to jump the gun with something that needs retracting.
Thanks. My head was starting to spin.
So I've updated the spreadsheet with a Comparison of Table 4's major elements with the actual calculated masses of the elements in the un-leached fly ash.
The first thing is still the units are incredibly off, but even if you shoehorn it into a percentage the actual values don't make sense either. He seems to have correct figures for Silicon (22.7%), but then Aluminum is 7, when it should be 14, Calcium 4.03 when it should be 3.78
It's incredibly sloppy, but difficult to explain how sloppy it is.
Elemental mass percentage is calculated by figuring the percentage of the element, based on the the molar mass of the element (and oxygen) and the number of atoms. Like:
This percentage is then multiple by the percentage of the oxide in the sample to get the percentage of the element in the sample.
Take a guess how long it took me to figure out what a "logarhythm scale" was these two sites made it easier for me.. if maybe someone wants to try to explain that aspect in a seperate 'general discussion' thread that can be linked too ??
i cant comprehend at all.
means and medians and ratios..
Another thing, his justification for normalizing to aluminum:
Seems specious, as the figures are already in ratio form. All this does is force the aluminum figures to be exactly the same. Normalizing to aluminum would only make sense if it were mixed in with some different elements you wanted to exclude from the total mass of the sample.
This paper could not have passed substantive peer review by anyone acquainted with environmental forensics.
With data unpublished the paper could not have been reviewed and without experimental details the experiment cannot be reproduced, then he also failed to provide a control...... All of that is a requirement for publication.
The Publisher states:
Does anyone know what he is referring to exactly by "At a 99% confidence interval, they have identical means (T-test) and identical variances (F-test);" What figures is he using to calculate this?
He wants to compare leachate with rainwater, which may be diluted. Normalizing to aluminum eliminates dilution effects.
BTW we are in a thread about the Current Science paper but we are analyzing the IJERPH paper.
It's a perfectly cromulent method of determining the percentage of how much of a sample came from Source 1 and how much came from Source 2. Determining how much plutonium leaked from Fukushima, for example, is confounded by the fallout from nuclear weapons testing. But each source has certain combinations of radioactivity ratios or mass ratios that make determining the percentages relatively easy. For example, the radioactivity ratio of Pu-238 to Pu-239+240 from Fukushima is 2.5; but from global fallout of nuclear weapons it is 0.026. If a sample has that ratio at 2.0 then the fraction that came from Fukushima is (2.0-.026)/(2.5-.026) = 80%
Herndon didn't approach it from that angle though. For him it was a black or white hypothesis.
T-test and F-test are used to compare two samples. So I guess he applied the tests to each element/aluminum ratio. Which is invalid because of multiple comparisons, although here none of the differences were significant (if we believe him), so it doesn't matter anyway.
The F-test is sensitive to normality, and the Moreno data are very non-normal, so the F-test is not applicable here anyway.
What I don't understand is why he included the Al/Al ratio. Should we be surprised that 1=1?
There are so many problems with this paper, any reviewer should have immediately rejected it.
I'm going to have a single summary post for both, as the problems overlap - both using Moreno badly.
It might be interesting to ask Weidan Zhou, Herndon's statistical advisor, about the statistical work in this paper.
I've begun to summarize things in the OP.
Just to clarify, it's used to compare the means and variances of samples from two populations/treatments, or in some cases, to compare those values from one sample set to a value that represents the null hypothesis. You can't do a T-test or F-test to compare two individual numbers; these are tests that use the sample variance (a measure of how "spread out" the individual measurements are in a sample) as part of the calculation. So, in this case he must have compared the means of the ratios in any such test, but then showed the ratio of the means in his figures.
Unfortunately this kind of thing is not easy to explain in a simple and clear way, with no maths. The most important problem with his analysis is that he's drawing conclusions from F- and T-tests that, by design, can't be made from those tests. But the general public can't be expected to grasp this. It's the sort of thing that peer-review is supposed to filter out.
^This.^ If it was reviewed by qualified peers, they did an embarrassingly bad job of it.
I made an infographic to illustrate the top post
Easy to change, so please let me know of correction or suggestions
Well, most of these problems are minor and due to sloppiness. The major problem is the complete invalidity of the "fingerprinting" method as he didn't validate the method, i.e. he didn't show that this method can actually distinguish coal fly ash in a set of minerals of crustal origin. E.g. he should have collected a range of uncontaminated soil/rock samples (e.g. from the San Diego area) and used their composition as controls/decoys to validate the fingerprint.
Basically, in order to develop a method to recognize whether some sample of minerals is coal fly ash or not, some type of classifier should be trained and validated on a sufficiently large set of known fly-ash and non-fly-ash samples. Then if we manage to develop a reliable classifier with low false positive/false negative rates, we can apply it to the rainwater and air samples. (It is doubtful, though, that such a classifier can be built as the composition of coal fly ash is so diverse that probably it cannot be meaningfully distinguished from other crustal material; except maybe the lack of carbon may be indicative.)
Here, no classifier was trained, no negative or positive controls were used, and the match was completely arbitrarily determined. Even the applied statistical tests were inadequate and incorrectly interpreted. So the paper is 100% junk science and totally invalid.
On the animation, can you vertically flip the data points before sliding them over?
That bit's not so easy, as I did it in Photoshop, which only has position animation.
I have sent him a message.
the detailed science/math is way beyond me, but from your post
in essence unless you know what "wrong (or right)" looks like, you can't ascertain what "right (or wrong)" looks like
just sloppy science not establishing a baseline
Actually you can transform things in Photoshop, they just need to be smart objects.
It's just a fancier and more complex version of the same old false claims about water and soil testing and that things like aluminum shouldn't be found there.
With my new found flipping skill....
although if you look at it long enough looks like the credits sequence of (multiple) Bond movies
@Mick West, can you add text describing what is shown? Such as "Fig. 6 as published by Herndon", "white data set flipped vertically", "exact match!", etc. I separated and flipped the data sets myself and I am having a hard time recognizing when it starts and what it is supposed to show.
It's a little fiddly to retime
i would ditch the Herdon opening text. we already know its a herndon graph and it just fries the brain trying to read that fast.
I have received a reply from Weidan Zhou (whom Herndon acknowledged for professional statistics advice). He has asked me to post his following statements regarding Herndon's paper here:
That's definitely information that should be in the OP, nice one.
Sylvain Henry wants to get dr. Herndon to the Paris Climate Change Conference:
I don't like the OP as it focuses on minor issues and appears to be nitpicking. The major issue is the one I described in #179.
It's a work in progress - I intended to get a lot more stuff. The challenge here is to make it reasonably accessible, and I'm open to suggestions. I'm a bit held back by my limited understanding of statistics.
I've added the Zhou email statement, which is pretty damning - his own advisor told him that his statistical analysis was incorrect.
as a layman i cant understand post #179. i always think its great to have 'advanced' scientific analysis but i think such things also need to be explained better at a layman level. if the goal is to reach/teach the masses.
i also think there is too much info (all mixed together) in this one thread for laymen. perhaps each individual point in the OP (when its done) can have a link to a seperate thread that explains that ONE aspect better. ??
and just cause naggin is what i do best:
more bullets vs. block text.
start with CLAIM in 'ex' tags
even font changes may help ease complicated debunks
understanding increases alot once you realize what a logarythmic scale is.. which the bulk of mainstreamers dont!
I'm not sure I understand what this means: "Described his question..." Is that a typo?
Yeah, I this is the real difficulty - explaining the problems in a way that is clear and accessible to anyone. I've passed at least a half-dozen statistics courses, and I still have to go back and look things up regularly when I put it into use. When discussing this with non-scientists, you don't want to get bogged down with the statistical nuances. But the most important, fundamental problems are pretty easy to state:
-If rainwater contains elements in ratios similar to coal ash, that doesn't mean that those elements came from coal ash; they could have just come from dust and dirt (which Herndon doesn't even consider).
-And Herndon's numbers don't even show that they're very similar, even though he clearly faked some numbers, and got other numbers wrong.
-And even with all that, he used an incorrect statistical analysis (could just give the quote from Weidan Zhou to support this at first).
You can state those key points at the top, and then start digging into evidence and details for those who are so inclined.
The plague of pay-to-publish "open access" journals is bad enough, but as I understand it, Current Science doesn't even have that excuse. I really wish an editor from that journal would join us to defend their decision to publish that paper. Or, any reviewer for either article.
Weidan Zhou has asked me to post this clarification here:
Separate names with a comma.