RollingThunder
Gold Member
- Mar 22, 2010
- 4,818
- 525
It does correlate with it, but correlation is not causation.Thank you for confirming that you are dodging the observation that the difference in the lows of each leveling off period quantifies man's contribution to global warming.The obvious?
There is no science demonstrating the significance and/or magnitude of the contribution of man made CO2 to any warming.
That surely is obvious.
As I haven't ever commented on that, it is impossible that I ever denied or confirmed it.
Thus, my lack of comment.
Some of you denier cult nutjobs are certainly fixated on your mantra of "correlation is not causation". Too bad for you that the statement is poorly framed scientifically even in the sense you mean it and it is also a logical fallacy in it's own right, in the way you use it. And of course, as is always the case with your denier cult drivel and pseudo-science, it is quite meaningless in relation to the reality of global warming.
First of all, the correct way to express this concept clearly in the sciences is: "Correlation does not necessarily imply causation."
Two things that show heavy correlation do indeed sometimes have a causational link. While correlation doesn't necessarily imply causation, it can be part of the evidence for causation.
And of course there are multiple lines of observed evidence for the reality of anthropogenic global warming. Climate scientists are not at all depending on statistical correlation to know that AGW is true, as you anti-science denier cult retards seem to imagine. I've already responded to your idiotic claim that there is no scientific evidence causally linking mankind's CO2 emissions to the current abrupt warming trend a number of times, like in post #135 of this thread but you are too much of retarded troll to admit that you were wrong and there is in fact a lot of good science linking the two. Remember, you moronic little dipshyt.....
Empirical evidence that humans are causing global warming
And now, the logical fallacy you're engaging in....
How To Argue
The New England Skeptical Society
(excerpts)
Confusing correlation with causation
This is similar to the post-hoc fallacy in that it assumes cause and effect for two variables simply because they occur together. This fallacy is often used to give a statistical correlation a causal interpretation. For example, during the 1990s both religious attendance and illegal drug use have been on the rise. It would be a fallacy to conclude that therefore, religious attendance causes illegal drug use. It is also possible that drug use leads to an increase in religious attendance, or that both drug use and religious attendance are increased by a third variable, such as an increase in societal unrest. It is also possible that both variables are independent of one another, and it is mere coincidence that they are both increasing at the same time.
This fallacy, however, has a tendency to be abused, or applied inappropriately, to deny all statistical evidence. In fact this constitutes a logical fallacy in itself, the denial of causation. This abuse takes two basic forms. The first is to deny the significance of correlations that are demonstrated with prospective controlled data, such as would be acquired during a clinical experiment. The problem with assuming cause and effect from mere correlation is not that a causal relationship is impossible, its just that there are other variables that must be considered and not ruled out a-priori. A controlled trial, however, by its design attempts to control for as many variables as possible in order to maximize the probability that a positive correlation is in fact due to a causation.
Further, even with purely epidemiological, or statistical, evidence it is still possible to build a strong scientific case for a specific cause. The way to do this is to look at multiple independent correlations to see if they all point to the same causal relationship. For example, it was observed that cigarette smoking correlates with getting lung cancer. The tobacco industry, invoking the correlation is not causation logical fallacy, argued that this did not prove causation. They offered as an alternate explanation factor x, a third variable that causes both smoking and lung cancer. But we can make predictions based upon the smoking causes cancer hypothesis. If this is the correct causal relationship, then duration of smoking should correlate with cancer risk, quitting smoking should decrease cancer risk, smoking unfiltered cigarettes should have a higher cancer risk than filtered cigarettes, etc. If all of these correlations turn out to be true, which they are, then we can triangulate to the smoking causes cancer hypothesis as the most likely possible causal relationship and it is not a logical fallacy to conclude from this evidence that smoking probably causes lung cancer.