With that being said, I knew that a million and one think pieces would be written: The one thing these outlets were so smug in their reporting while often getting it wrong or not understanding the nuances of a work like this.
The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. The current subprime crisis has been doing wonders for the reception of any ideas about probability-driven claims in science, particularly in social science, economics, and "econometrics" quantitative economics.
But it was easy to see from the past that the pilot did not have the qualifications to fly the plane and was using the wrong navigation tools: The same happened in with money center banks losing cumulatively every penny ever made, and in when the Savings and Loans industry became history.
I want this to stop, and stop now— the current patching by the banking establishment worldwide is akin to using the same doctor to cure the patient when the doctor has a track record of systematically killing them.
And this is not limited to banking—I generalize to an entire class of random variables that do not have the structure we thing they have, in which we sample college essays nyu bookstore be suckers.
And we are beyond suckers: Are we using models of uncertainty to produce certainties? This masquerade does not seem to come from statisticians—but from the commoditized, "me-too" users of the products. Professional statisticians can be remarkably introspective and self-critical.
Recently, the American Statistical Association had a special panel session on the "black swan" concept at the annual Joint Statistical Meeting in Denver last August.
They insistently made a distinction between the "statisticians" those who deal with the subject itself and design the tools and methods and those in other fields who pick up statistical tools from textbooks without really understanding them.
For them it is a problem with statistical education and half-baked expertise. Alas, this category of blind users includes regulators and risk managers, whom I accuse of creating more risk than they reduce.
A map is a useful thing because you know where you are safe and where your knowledge is questionable. Now once you identify where the danger zone is, where your knowledge is no longer valid, you can easily make some policy rules: So the principal value of the map is that it allows for policy making.
Indeed, I am moving on: While most human thought particularly since the enlightenment has focused us on how to turn knowledge into decisions, my new mission is to build methods to turn lack of information, lack of understanding, and lack of "knowledge" into decisions—how, as we will see, not to be a "turkey".
This piece has a technical appendix that presents mathematical points and empirical evidence. It includes a battery of tests showing that no known conventional tool can allow us to make precise statistical claims in the Fourth Quadrant.
But that is not the main problem with research. For us the world is vastly simpler in some sense than the academy, vastly more complicated in another. So the central lesson from decision-making as opposed to working with data on a computer or bickering about logical constructions is the following: In some situations, you can be extremely wrong and be fine, in others you can be slightly wrong and explode.
If you are leveraged, errors blow you up; if you are not, you can enjoy life. In the real world, there are very few situations where what you do and your belief if some statement is true or false naively map into each other. Some decisions require vastly more caution than others—or highly more drastic confidence intervals.
You do not need "evidence" that a gun is loaded to avoid playing Russian roulette, or evidence that a thief a on the lookout to lock your door. You need evidence of safety—not evidence of lack of safety— a central asymmetry that affects us with rare events. This asymmetry in skepticism makes it easy to draw a map of danger spots.
The Dangers Of Bogus Math I start with my old crusade against "quants" people like me who do mathematical work in financeeconomists, and bank risk managers, my prime perpetrators of iatrogenic risks the healer killing the patient.
A Turkey is fed for a days—every days confirms to its statistical department that the human race cares about its welfare "with increased statistical significance".
Yet bankers kept their previous bonuses and it looks like citizens have to foot the bills. And one Professor Ben Bernanke pronounced right before the blowup that we live in an era of stability and "great moderation" he is now piloting a plane and we all are passengers on it. As I show in the appendix, this is typical with ANY socio-economic variable commodity prices, currencies, inflation numbers, GDP, company performance, etc.
No known econometric statistical method can capture the probability of the event with any remotely acceptable accuracy except, of course, in hindsight, and "on paper". Also note that this applies to surges on electricity grids and all manner of modern-day phenomena.
Figures 1 and 2 show you the classical problem of the turkey making statements on the risks based on past history mixed with some theorizing that happens to narrate well with the data. A friend of mine was sold a package of subprime loans leveraged on grounds that "30 years of history show that the trade is safe.
And the unusual dominance of the rare event shown in Figure 3 is not unique: Now let me tell you what worries me.Links to Publishers at the complete review. See also separate pages with links to: Book Review sites | Literary Weblogs | General Literary sites (Inter)national Literary sites.
Most listings of links to publishers are either too broad -- every publisher under the sun -- . This is the foliage of destiny. Over the past year I have read and responded to many questions from bright, eager high school students who want to know if they have what it .
Alessandro Acquisti, Associate Professor, Information Technology and Public Policy. Alessandro Acquisti is a Professor of Information Technology and Public Policy at the Heinz College, Carnegie Mellon University (CMU) and an Andrew Carnegie Fellow (inaugural class).
Founded in by teachers and scholars, the Modern Language Association (MLA) promotes the study and teaching of language and literature. Online shopping from a great selection at Books Store.
Blending elements of memoir and sports writing, Anelise Chen’s debut novel is an experimental work that perhaps most resembles what the ancient Greeks called hyponemata, or “notes to the self,” in the form of observations, reminders and self-exhortations.