Statistician to the Stars!
I had the knife at my throat after reading a paper by Preti, Lentini, and Maugeri in the Journal of Affective Disorders (2007 (102), pp 19-25; thanks to Marc Morano for the link to World Climate Report where this work was originally reported). The study had me so depressed that I seriously thought of ending it all.
Before I tell you what the title of their paper is, take a look at these two pictures:
The first is the yearly mean temperature from 1974 to 2003 in Italy: perhaps a slight decrease to 1980-ish, increasing after that. The second pictures are the suicide rates for men (top) and women (bottom) over the same time period. Ignore the solid line on the suicide plots for a moment and answer this question: what do these two sets of numbers, temperature and suicide, have to do with one another?
If you answered “nothing,” then you are not qualified to be a peer-reviewed researcher in the all-important field of global warming risk research. By failing to see any correlation, you have proven yourself unimaginative and politically naive.
Crack researchers Preti and his pals, on the other hand, were able to look at this same data and proclaim nothing less than “Global warming possibly liked to an enhanced risk of suicide.” (Thanks to BufordP at FreeRepublic for the link to the on-line version of the paper.)
How did they do it, you ask? How, when the data look absolutely unrelated, were they able to show a concatenation? Simple: by cheating. I’m going to tell you how they did it later, but how—and why—they got away with it is another matter. It is the fact that they didn’t get caught which fills me with despair and gives rise to my suicidal thoughts.
Why were they allowed to publish? People—and journal editors are in that class—are evidently so hungry for a fright, so eager to learn that their worst fears of global warming are being realized, that they will accept nearly any evidence which corroborates this desire, even if this evidence is transparently ridiculous, as it is here. Every generation has its fads and fallacies, and the evil supposed to be caused by global warming is our fixation.
Below, is how they cheated. The subject is somewhat technical, so don’t bother unless you want particulars. I will go into some detail because it is important to understand just how bad something can be but still pass for “peer-reviewed scientific research.” Let me say first that if one of my students tried handing in a paper like Preti et alia’s, I’d gently ask, “Weren’t you listening to anything I said the entire semester!”
Background
You often hear, if you manage to stay awake during the lectures, a mathematician or physicist say, “The following is a necessary but not sufficient condition for my theory to be true.”
We say this so often that we tend to blend the words together: necessarybutnotsufficient, and we forget that it can be a confusing concept.
It means that there is an item or a list of items that must be the case in order for my theory to be true. But just because that item or those items on that list are true, it does not mean that my theory must be true. It could be the case that the item is true but my theory is false.
This is all important in the theory/model building that goes on in the sciences.
For example, it is necessary but not sufficient that my theory be able to explain already observed data that I have collected. If I cannot at least explain that data, then my theory cannot be true. This is necessarybutnotsufficient in the weak sense: all theories must be able to explain their already-observed data.
Again, it is a necessary but not sufficient condition that my theory be able to explain future data. This is necessarybutnotsufficient in the strong sense: if my theory is right, it must be able to explain data that is not yet seen.
Understand: it can still be the case that my theory can predict data that is not yet seen and my theory could be false. This is true in all cases where we cannot deduce (know with certainty) the true of a theory. Most theories (outside math) are not, of course, deduced.
How about an example? Let’s us the following game.
The Game
Go to The Philosopher’s Mag and play this game called “Dealing with Induction”. It asks the question: “how easy is it to draw a wrong conclusion about the future from the evidence of the past?”
The game tests your inductive reasoning skills and asks you to infer the rule that accepts or rejects cards from a standard 52-card deck.
Let me be as clear as possible. The following conditions hold: (1) You believe that a rule that generates the card exists. (2) You will see a sequence of cards from which you will attempt to infer, through induction, the rule. (3) No matter how many cards are shown you will never know the rule with certainty; that is, you will never be able to deduce the rule from a set of premises.
Do not read further until you have played the game fully and discovered its secret.
Did you really play?
Tell the truth. Don’t cheat and read any more until you have played the game.
