Talk-Polywell.org

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http://wmbriggs.com/blog/?p=1958

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Also Yes, if by “has warming occurred?” we really mean “Has the temperature increased so that is higher now than it was fifteen years ago, but I also allow that it might have bounced around during that fifteen years?”

Each of these qualifiers corresponds to a different model of the data. Each of them has, that is, a different probabilistic quantification. And so do myriads of other model/statements which we don’t have time to name, each equally plausible for data of this type.

Which is the correct model? I don’t know, and neither do you. The only way we can tell is when one of these models begins to make skillful predictions of data that was not used in any way to create the model. And this, no climate model (statistical or physical or some combination) has done.

I scanned it, but it looks stupid. Statistical significance is perfectly straight forward as long as you keep a "normal" head.

The question is, what is the probability that this data set came from a data set whose trend was upwards (or downwards, or whatever criterion you suggest). Ordinarily you look for a k=2 significance, i.e. better than 95%.

It might be that the data indicates a 75% probability that there is warming. But that would not necesarily be "statistically significant", dependent on the spread of the data. Clearly the spread of the data is going to be high, so I would expect that the distribution of data tells Phil not to accept anything much than 90% before it is statistically significant. Maybe it is higher still but he's keeping a few cards. I dunno. But I've always found Phil Jones to be straight forward and candid and I think it is unfair to be focussing on him. There are plenty of other players in this thing that have taken his results and made political capital from them; I'm not aware that he's ever said "the debate is over" &c., but plenty of others have. Large data sets and simulations always require a creative flare in manipualting the outputs, I feel Phil may have fallen into the trap of not being particularly clear in what those means and methods ("tricks") may have been, but it is par for the course in ALL scientific research that uses large data sets and/or simulations that generate such data sets. The key is to make your assumptions clear and reasonable, but this is widely ignored across many academic "disciplines" these days, climatology is not unique in this, it has merely come under a closer scrutiny.

Darn, I was hoping global warming was for real. I could get to love springtime weather in Febuary and never having to shovel it. They're using helicopters to carry containers full of snow to the Olympic ski slopes today.