Remember that hockey stick?Follow

Yeah, all tell tale signs for sure. It's really hard to pull the trigger on that kind of thing though, especially prior to publication. It's one thing to think the data looks suspiciously good, and another to hold up publication and ask the submitter to go collect more data. Especially since anything like that will likely be taken to an additional reviewer, and they'll likely have to think the same thing. More likely it gets passed though with reservations, and they wait for others to try and replicate the experiment and confirm their suspicions. Whether or not that happens though...

The whole "I don't think you're innocent, but I can't prove you're guilty" thing, basically.

I guess. Still, after years of this you'd expect people to catch on. But I guess it's different people who reviewed his work every time.
It took the 3 students who caught him months to gather the needed evidence even though they knew he was cheating all that time (and hurting people who used his data).

Why do you go to such great lengths of written word when a simple "I categorically deny any understanding of the subject whatsoever" would suffice?

I've already given you a few examples of areas relied upon by that particular graph which are currently in dispute by climate scientists as to the margin of error for early timeframe analasys. If X+Y=Z, but X+Y are potentially different values than what they were plotted on Graph point Z, that potential variance is called a "margin of error" Statistically, the margin of error they are showing for the 10,000 year old values in particular, is utter crap, because the individual variables themselves presently have statistical uncertanties even within their own climate change scientist community that they are flat out ignoring. They picked a set of assumptions, and made a graph. They didn't include any of the uncertanty factors, and from what I have seen they didn't even use the assumed Median values in their uncertanty calculations. They picked data, made a graph to show a particular viewpoint without giving it a sufficient margin for error, and sent it to press. Thats ignoring the whole quality of sample issue from that far back entirely.


Sure. but only assuming a 0.4 degree +/- margin of error for that data the way they did on the graph based on the underlaying uncertanty and currently disputed variables of the model is being scientifically dishonest if nothing else for the older data they added. The margin of error should quite obviously widen considerably on anything older than 2,000 years as it approaches 10,000 years and our measurements and observable datasets become much more uncertain due to the effects of time and variables we have no historical observational data for. Especially when there is not consensus on early model timeframe climate condition variables which were used to create that model. The basic data and methodology are not at issue here. It's the accuracy of the older datasets, and the currently contradictory theories on various important factors as mentioned previously in the thread that is the problem. Their error bars are crap on the left side of the graph. You seem to think otherwise but provide no evidence to the contrary.


It's not "too hard" It's "impossible" to create that particular graph with that narrow a margian of error without ignoring valid, though less popular (note I don't say "correct") studies that show a greater range of uncertanty on the oldest data sets on variables used to make their graph model. Our resolution of data accuracy degrades significantly the further back you go, and our uncertanties rise. There is a degrading confidence interval on the earliest data sets and a larger margin for error that is not reflected on their graph, which has been my point all along.

Would some diagrams with large arrows on them pointing at simple concepts help? Maybe I could toss in an animated dancing frog or in the margins or something if that would make this easier for you to understand.

They picked data, made a graph to show a particular viewpoint without giving it a sufficient margin for error, and sent it to press.

I don't see an evidence for this. Some, anything, could possibly change me point of view. Thusfar, it seems like you want that taken on faith, essentially, or with arguments from "there's no way you can know this".

I can sling chi-squares and probability curves around just fine, and I make a Mean Median ala Mode. My Coinfidence Intervals regarding my ability to interperet and generate stochastic statistical analysis models and assorted regression analysis curves remains high. I'm starting to wonder if you failed your course though. Perhaps if you tried presenting an argument other than "I don't think you understand this so you're wrong" might be in order? Because I really do. Honest.

If you come up with a decent argument, let me know. Thanks!

Well Lets take a look at what they wrote



So, they started with a random Monte Carlo set to trim off Uncertanties (or skew the data away from dissenting records), and then based their entire graph on 80% marine climate data. That's the whole "number of fossil marine critters per given geological strata layer" and :Carbon dissolved in lime stone per geological strata layer" data for the most part, amongst other metods, and pretty much ignoring any other sources. The problem with marine strata layers is they have a high degree of inherent uncertanty due to the errosive power of water. Terrestrial strata layers are much less prone to having thousands of years of muck suddenly ripped away by a particularily powerful storm surge across a large swath of your sample area for example. The further you go back using such records, particularily marine records, the more uncertanties you encounter as to the accuracy of the observable strata. They attempt to offset that by saying "well, we know that this critter that still exists dies off at this rate today in laboratory cultures, so they must have still died off and deposited at that rate under conditions found at that location 10,000 years ago, because obviously temperature, pressure, acidity, water clarity etc. factors for water bodies don't ever change significantly over time, not to mention genetic drift factors, etc., and using multiplecore samples from independant firms, all of which may or may not have been subject to significant alterations in topology over the last 10,000 years with no way for anyone at all to know. Their first paragraph basically flat out says "our data gets worse the further you go back, but it's ok because our method magically provides better information over long periods of time because we're awsome and you don't need to see our actual math work" They plotted what they think the line should be after "adjusting" their sample set, mixing progressivly lower resolution data with modern higher resolution data with no adjustment for increased uncertanties. The fact that they aren't showing a greater temperature uncertanty for the oldest data and won't release their mathmatical model tells me something isn't right here.

They are really annoying though. Black box software in research makes me want to hurt things.

Lies are bad.

Also this jumped to mind.

I don't remember much geology

How about science book or the French you took?