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| Sun Jun 15 22:23:08 2008 Sasquatch 2008 |
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| Sun Jun 8 16:39:28 2008 Forbes: Fooled by Randomness! |
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| Tue Jun 3 22:38:01 2008 Fooled By Randomness |
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| Sun Jun 15 22:23:08 2008 Sasquatch 2008 A geek's report on the music festival. |
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| Yes, I'm late! I was at the Sasquatch 2008 Music Festival over Memorial Day weekend (24 - 25 May), but I'm just now getting to writing it up. The weather varied between beautiful and bad. When beautiful, you remembered why you went to The Gorge--a dramatic landscape with beautiful skies. When bad, you were treated to cold and relentless rain. Another Sasquatch 2008 reviewer mentioned "fans put up with sideways rain," because of the wind. 
There was a great lineup (you can see for yourself). They had several great headlining bands, such as R.E.M. and The Cure. But I was most excited to see some of the other bands that I hadn't seen in concert before, such as Death Cab for Cutie and Modest Mouse.
Between bands, I would marvel at the crowds. From our vantage point (almost directly back from the center of the stage both days), we could see the thousands of people moving back and forth. It was a great example of emergent phenomena, watching all the invidivuals combine into an overall flow of people that could probably be well-modeled by fluid dynamics. In general, a band would play, and then there would be net outflow of people towards the bathrooms, food areas, and other stages. Towards the beginning of a set, the flow would reverse. As popular (and direct) routes got busy, people would naturally choose less congested routes.
A beer cost $8 (more for "premium" beers). The economics of food pricing at festivals is interesting. Of course, as a captive audience, you know you'll be charged an arm and a leg for average food--it's the same as the movie theater. In fact, this phenomenon (high price of popcorn at movie theaters) is well-known and studied by economists a lot. This recent blog entry has a long discussion on it! But the short answer is that the high prices are probably close to the real value--after all, thousands of people pay the prices that are charged! It's just that the real price of the item isn't usually related to the cost of the ingredients: instead, most of the price is the labor of making the item, and (most importantly) the convenience to the consumer. I brought my own food, but occasionally I wanted something hot. For the occasional hot snack, why not pay a bit more? The convenience factor was high. For beer, the choice was between their prices or no beer at all. So they picked a price point to maximize return, where higher prices would drive more people away, and lower prices would mean selling too cheaply. Of course, there is another cost that means festivals will charge more: drunk patrons are a pain to manage. But if you're going to talk about the economics of music, it's more than beer and food prices. It is the disintegration of the standard music distribution business (see this article from Fox News or this article from The Week). CD sales are plummeting, and digital revenue isn't coming close to replacing it. I'm not sure I care about the music distribution companies--their industry may disappear, and them with it. Today we don't cry about the disappearance of coopers (barrel makers), even though their industry long since collapsed (although did not disappear entirely). No, the danger is to bands themselves. How will bands make money in the future? Probably by a combination of live performances (which accounted for most of their revenue under the old system anyway) and their own direct digital sales of their music (like what Radiohead did). For a great summary, see this report, commissioned by the Department of Canadian Heritage. For an American, it's weird to see governments funding this sort of thing, but it is an interesting report.
Top 3 bands? This is my list, although I was only there for 2 days, and only at the Main Stage:
I hadn't heard of Tegan and Sarah before, but I thought they were excellent. I've since added a bunch of their tracks to my collection. Don't get me wrong: there were a lot of great bands there, and the Presidents rocked. But those are my top 3.
As much as I studied the crowd behavior and economics of festival food prices, I was also impressed by the selection of bands at the festival. The lineup was well-done, for the quality of (most) bands and especially for the variability. I guess putting together a festival lineup is a bit like making a good mix tape (or CD or playlist...), only much larger in scale. Comments |
Related: > mathematics < economics lists Unrelated: books energy environment geopolitics predictions science |
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| Sun Jun 8 16:39:28 2008 Forbes: Fooled by Randomness! Forbes flubs basic statistics. |
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| In my previous entry (
Fooled By Randomness) I reviewed a book that pointed out all of the mistakes people make with
statistics.
I had to laugh, then, when Forbes came out with their list of most dangerous sports (see the slideshow here). The list is NOT the list of the most dangerous sports! It is just a list of where the most sports injuries occur. As the authors point out: "The rankings do not take into account varying participation rates, which partly explains why many popular sports yielded the greatest number of injuries." Put another way: the Forbes list gives you NO idea which sport is the most dangerous. A more accurate name would be "The most popular sports in the US as measured by injuries." For instance, on their list, jumping out of a plane without a parachute would count as a very safe sport, since it happens so rarely. And BASE Jumping didn't even make the list. Basketball (!) was what Forbes considered the most dangerous sport, well ahead of American Football and BASE Jumping. The list is interesting, but clearly it doesn't tell you anything about danger. (I mean, come ON! Watch this BASE jumping video and tell me that basketball is remotely dangerous.) In order to determine how dangerous a sport is, you need to figure out NOT the absolute count of injuries, but the RATE of injuries. A better question is: "If I play this sport regularly for a month, what is my chance of getting injured?" (Where "regularly" depends on the sport). If you do searches for Dangerous Sports, you'll get a bunch of useless results. Again, people confuse the absolute number of injuries with the rate of injuries. I started to get worried. Maybe no one who studies sports has any concept of probabilities? For a second, I had high hopes for a 2003 article that studied sports injuries in the US from 1997 - 1999 (you can find the article at The British Medical Journal's website). It claimed to have normalized data, with injury rates. However, all they did was divide the injury rates by the population size! So again, popular sports ranked highest. Not surprisingly, Basketball was at the top of the list. That was sobering. Yikes! Even doctors studying sports injuries had gotten it wrong. (Although, to be fair, they weren't trying to compile a list of the most dangerous sports. But wouldn't that be useful?). More digging turned up a few numbers. This book had some useful data, although limited. It noted that the most dangerous sports it surveyed were Rugby (59.3 injuries per 100 participants in 4 weeks), Soccer (39.3), Martial Arts (36.3), Hockey (24.8), and Cricket (20.2). That is exactly the sort of data that can help you define dangerous sports! And I don't think it's too much surprise that rugby is near the top. (Obviously that was a British book). Then this link had data on skiing and snowboarding. They measured rates in terms of injuries per 1000 ski days (on average, how many people are injured on a day with 1000 people on the slopes, for instance). To convert that to the other metric (number of injuries per 100 participants in 4 weeks) I had to guess how often your average skier/snowboarder went per week. Assuming 10 visits to the slopes in 4 weeks (all weekends and two extra days), that yields an injury rate of 3 injuries per 100 participants in 4 weeks for Skiing, and 4 for snowboarding. (I think those numbers are slightly lower because the study only counted injuries requiring medical attention). Based on that site, Skiboarding had rates of 8 injuries per 100 participants in 4 weeks, while Nordic Skiing was lowest around 0.4. Then this article had more data. According to the NCAA, the most dangerous college sports are spring football (9.6 injuries per 1000 participants), men's wrestling (5.7), women's soccer (5.2), and men's soccer (4.3). Men's fall football was only 3.8 injuries per 1000 participants. To convert those numbers (injuries per 1000 participants) to the above (injuries per 100 participants over 4 weeks) I had to guess how many weeks people participated in college sports. I assumed 12 weeks per season. Doing the math (converting 12-week injury rates to 4-week injury rates) yields 0.32 injuries per 100 participants in 4 weeks for spring football, 0.19 for men's wrestling, 0.17 for women's soccer, 0.14 for men's soccer, and 0.13 for men's fall football. I searched around a bit more, but was unable to come up with much more data. Here then are my results. Most Dangerous Sports This is an Internet exclusive! I don't think anyone has a decent compiled list of actual dangerous sports (again, other lists are just most common injuries due to popular sports). The most dangerous sports, measured by the number of injuries per 100 participants over 4 weeks:
That's not a very good list, because so many popular sports are missing, and I had to make a lot of assumptions to put it together. But that's because no one has measured or compiled the data in any useful form. Despite years of Forbes lists, it turns out that no one, not even sports physicians, have actually determined what the most dangerous sports actually are! Comments |
Related: > mathematics < Unrelated: books economics energy environment geopolitics lists predictions science |
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| Tue Jun 3 22:38:01 2008 Fooled By Randomness A book report. |
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| I recently read (well, re-read) Nassim Taleb's
Fooled By Randomness, subtitled "The Hidden Role of Chance in Life and the Markets."
It is an excellent book, well-worth reading for two reasons:
I had two main take-aways. The first take-away was a deeper appreciation for the Survivor Bias, which occurs when a supposedly statistical study fails to include all data properly. In finance, it is common to compare only long-lived mutual funds (for example) and ignore all of those that have failed. It is very sobering to realize that if you put a bunch of people and funds into place, had them guess randomly about investments and tracked them over time, you would see many fail and a few survive for a long time (by chance)--exactly the same situation we observe today! Only we don't say long-lived or successful funds are random survivors. We say the fund managers are geniuses, and expect them to repeat their successes. (Again, soberingly, most don't). The second take-away was people's poor appreciation for probability. Even in his world of trading, where people with scientific and mathematics backgrounds were working on algorithmic strategies, there was a disconnect with simple statistics. Even basic concepts such as Expected Value were often missed! Nassim's main point was that a person well-versed in basic probability, and aware of the large role of randomness in the world, could avoid many common mistakes and maybe even make money off other peoples' ignorance. Certainly that's true in his profession. It isn't a perfect book. He extended some of the survivorship bias to good people management. I think enough of us have had good (and bad!) managers to know that good managers often aren't survivors--they are actually good managers. I see Nassim's point that sometimes managers get lucky (due to happening to manage an organization during a moment of critical success or riding a market bubble, etc.), so a few "star" CEOs may actually be just average managers who happened to be at the right place at the right time. But some of his arguments here felt a bit jaded. Still, an overall enjoyable read, and a good reminder while the markets are in their current volatile state. I don't know how Mr. Taleb did in the subprime mortgage crash, but given his stated preference for targeting large crashes, I suspect he did quite well. Comments |
Related: economics > mathematics < books Unrelated: energy environment geopolitics lists predictions science |
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