One key reason why we struggle to see progress in the world today is that we do not know how very bad the past was.
Tag: statistics
Cardiologists and Chinese Robbers
There are over a billion Chinese people. If even one in a thousand is a robber, you can provide one million examples of Chinese robbers to appease the doubters. Most people think of stereotyping as “Here’s one example I heard of where the out-group does something bad,” and then you correct it with “But we can’t generalize about an entire group just from one example!” It’s less obvious that you may be able to provide literally one million examples of your false stereotype and still have it be a false stereotype. If you spend twelve hours a day on the task and can describe one crime every ten seconds, you can spend four months doing nothing but providing examples of burglarous Chinese – and still have absolutely no point.
If we’re really concerned about media bias, we need to think about Chinese Robber Fallacy as one of the media’s strongest weapons. There are lots of people – 300 million in America alone. No matter what point the media wants to make, there will be hundreds of salient examples. No matter how low-probability their outcome of interest is, they will never have to stop covering it if they don’t want to.
Take Care of Your Choropleth Maps. Great overview of how some seemingly simple tweaks in the data limits, colors, etc. can result in a different story.
Tim Tebow and the Taxonomy of Clutch » Skeptical Sports Analysis. I was getting worried about the recent @skepticalsports drought, but those dark days are past for now.
Correlation or Causation? – Business Week.
Statistics are easy: All you need are two graphs and a leading question.
Charts, graphs, and tables are on the decline. But what’s that newcomer in blue? Infographics!
Those who decry statistics are often the first to cite a statistic with a sample size of exactly one.
Micromort – Wikipedia, the free encyclopedia
“A unit of risk measuring a one-in-a-million probability of death”. (via Lone Gunman, which blog I found via Link Banana)
The Joy of Stats – Tablet Magazine
Where before we silently cursed the dumb coach in our living room while remaining unsure whether we were pissed because we were right or because we had had four beers, today we take to the Internet and find thousands of people who also think we are right, and some more who have done the math that demonstrates that we are right, and therefore we know.
The Case for Dennis Rodman: Outline » Skeptical Sports Analysis
I love this whole series. Statistics class would have been so much better if these were the lessons. It makes both basketball and math a lot more interesting than you’d think.
The Case for Dennis Rodman: Outline » Skeptical Sports Analysis
Marginal Revolution: Sex and Statistics or Heteroscedasticity is Hot
Alex Tabarrok mulls over the recent OkTrends post on the Mathematics of Beauty.
I think there are certain types of beauty that greatly attract some men but repel others. Analagously, some people will pay hundreds of dollars for an ounce of caviar that other people won’t eat for free. The reason some people love caviar, however, is not that other people dislike it. Instead, it just so happens, that the thing that some people love is the very thing that repels others. We see the same phenomena in art, some people love John Cage, other people would rather listen to nothing at all. ;)
Now if we mix in this kind of beauty–beauty over which there are violent disagreements–with the kind that most people do agree upon (think Haagan-Dazs vanilla ice cream) then I suspect that it will appear that lower rankings increase messages. But what is really going on is that high rankings–conditional on their also being many low rankings–actually signal an extra strong attraction. Someone who tells you that John Cage is their favorite composer is telling you more than someone who says Aaron Copland is their favorite composer.
Marginal Revolution: Sex and Statistics or Heteroscedasticity is Hot
Marginal Revolution: Sex and Statistics or Heteroscedasticity is Hot
Alex Tabarrok mulls over the recent OkTrends post on the Mathematics of Beauty.
I think there are certain types of beauty that greatly attract some men but repel others. Analagously, some people will pay hundreds of dollars for an ounce of caviar that other people won’t eat for free. The reason some people love caviar, however, is not that other people dislike it. Instead, it just so happens, that the thing that some people love is the very thing that repels others. We see the same phenomena in art, some people love John Cage, other people would rather listen to nothing at all. ;)
Now if we mix in this kind of beauty–beauty over which there are violent disagreements–with the kind that most people do agree upon (think Haagan-Dazs vanilla ice cream) then I suspect that it will appear that lower rankings increase messages. But what is really going on is that high rankings–conditional on their also being many low rankings–actually signal an extra strong attraction. Someone who tells you that John Cage is their favorite composer is telling you more than someone who says Aaron Copland is their favorite composer.
Marginal Revolution: Sex and Statistics or Heteroscedasticity is Hot
Graph of the year – Statistical Modeling, Causal Inference, and Social Science.
Bill James (and others) have pointed out that true racial equality in baseball came, not when superstars such as Jackie Robinson and Willie Mays started joining major league rosters, but when there was room for ordinary black players to join their equally unexceptional white colleagues on the bench.
Similarly, graphical methods have truly arrived when journalists use graphs to make ordinary, unexceptional points in a clearer way. When making a graph, and including it in an article, is easy enough that it’s done as a matter of course.
Hans Rosling’s 200 Countries, 200 Years, 4 Minutes – The Joy of Stats – BBC Four. Showing the world’s progress along the axes of lifespan and income. Fascinating data and a wonderful narrator/performance. (via)
I love this post about measuring whether an artist is under- or over-valued. The method is pretty cool, basically comparing the Human Accomplishment ranking and the available Amazon music inventory, and making a rough P/E ratio. This post focuses on notable composers and it looks like Medieval, Renaissance, and Baroque composers get shorted, while late Romantics (especially opera dudes) get more hype than they deserve. And you see the same sort of bias in the season programming of most major orchestras.
Anyway, two cool things this brings to mind. One, I like this idea of bubbles in culture. Reminds me of the vast difference in New York Times coverage of conflicts in Darfur vs. the Congo, though one area has been about 10 times as deadly. There are all kinds of interesting feedback loops that affect how we perceive and respond to our world. And two, realizing that there’s so much rough-and-ready data out there that we’ve unwittingly created, just waiting to be mined.
Over the past 5 years, 32% of the New Yorker’s fiction came from 14 different authors. [via Pete Lit]