Fun with graphing

Global warming fans unite: Iowahawk shows you how to make your very own hockey stick graph!

It’s made much easier by the fact that you can feed it any data you like, and get the same graph nearly every time. Much more convenient, since it removes the need for messy data sets. Who has time and space for all that data? Relying on data to create graphs is just plain silly, when you think about it. Just build the desired graph into the modeling process! Done!

He also does the investigative and analytical work on climate research modeling that should have been done years ago by the “scientists” that did the “research” leading to the infamous hockey stick graph. But, hey, science is hard and stuff! And grant money flows more freely when you gin up the scare-mongering and create dramatic images that impress the easily fooled.

Key quote:

The devil, as they say is in the details. In each of the steps there is some leeway for, shall we say, intervention. The early criticisms of Mann et al.’s analyses were confined to relatively minor points about the presence of autocorrelated errors, linear specification, etc.  But a funny thing happened on the way to Copenhagen: a couple of Canadian researchers, McIntyre and McKitrick, found that when they ran simulations of “red noise” random principle components data into Mann’s reconstruction model, 99% of the time it produced the same hockey stick pattern.

For those unbiased, clear-headed types following along at home, this means that the hockey-stick shape is a creation of data manipulation. The graph has just about zero to do with the data itself.

The modeling process is the hockey stick graph, essentially. And the hockey stick graph is the modeling process. There is no distinction of note between the two.

Ponder that for a while. You could feed any kind of data you want into this process, and get almost the same graph every time. Hockey scores from 1994. Kirstie Alley’s waist size 1985-2000 in centimeters. Joe Biden’s IQ, multiplied by the number of hairs on his head, divided by the number of dumb things he says every day.

And that means that the graph, and the modeling process used to create it, are completely 100% invalid. Whatever you might want to call this — and I can think of a few things, some of them rhyming with fullship — it surely is not science. It’s not even in the same zip code.

But lots of quasi-important people have been thrusting this thing in our faces for a decade or more, with spittle flying from their lips, pointing maniacally at it and screaming that we have to believe it because it’s, like, Science, man! Fer sure!

Um, sorry, no it isn’t. And if Mann were a real scientist, he would have uncovered these flaws himself. But he didn’t, because he probably put them there himself. Maybe he just didn’t understand – the job of a scientist is to remove layers of confusion, not add them.

Science is so confusing sometimes!

Advertisements

Comments are closed.