by whologwhy
Articgate: Now THAT’s cherrypicking
[Via Deltoid]
This graph by Peter Gleick reveals the cherry pick used by Harrison Schmitt to claim that “Artic [sic] sea ice has returned to 1989 levels of coverage” and Heartland’s Joseph Bast to claim
“In fact, National Snow and Ice Data Center records show conclusively that in April 2009, Arctic sea ice extent had indeed returned to and surpassed 1989 levels.”
[More]
Take a look at the whole data. Look at it carefully, month by month. Then try and say this without feeling like a liar:
In fact, National Snow and Ice Data Center records show conclusively that in April 2009, Arctic sea ice extent had indeed returned to and surpassed 1989 levels.
The denialist toolkit is full of such attempts to ignore the majority of the data and find a few data points that fit their needs.
Do people really want to be on the side of such people, on the side of twisting data to mean what it obviously does not mean. This is not a case of statistics and such. For two weeks out of 52 there was more ice in 2009 than in 1989. This is only because melting started later in 2009. But every other week in 2009 is less than in 1989.
So, which is really important to people who want to let the facts show them the truth? The 2 weeks cherry-picked by denialists or the other 50?
How about we look at all the data? Look at how much 1989 is above the line. Then look at 2009.None of it is above the line. Look at the overall trend, not just the 2 weeks of data the denialists used but the entire 1666 week record.
Does it look like the denialists are correctly explaining all the data or are they just finding a few data points – perhaps 0.1 percent of all the data – to shore up their denialist argument?
Would it be a winning argument to say “I’m right one time out of a thousand? Would you put money in a bank that only had the right balance two weeks out of 32 years?
Cherry-picking is a favorite tool of the denialist. It is always easy to tell which side is the side of denialism. It the argument requires only looking at a small part of the data, rather than the bulk of the data, then chances are they are denialists.
Couple this with quote mining and you have almost complete verification of the denialist’s side.
A Man With A Ph.D. 
