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#161
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On Wednesday, May 22, 2019 at 4:56:53 PM UTC-7, AMuzi wrote:
On 5/22/2019 6:43 PM, Frank Krygowski wrote: On 5/22/2019 4:49 PM, jbeattie wrote: On Tuesday, May 21, 2019 at 2:07:39 PM UTC-7, Frank Krygowski wrote: On 5/21/2019 11:29 AM, jbeattie wrote: On Monday, May 20, 2019 at 4:10:56 PM UTC-7, Frank Krygowski wrote: On 5/20/2019 5:07 PM, jbeattie wrote: Tom, statistically, you did not have any of your head injuries. They were imagined... IOW: "Math is HARD!!!" It's not math. It's statistics -- where two plus two may equal four, depending on who you are. Large population studies say little or nothing about the risks encountered by individual cyclists in particular areas or engaging in specific types of cycling. Tom is an example -- as are most of my cohorts. It doesn't take a math genius to recognize that lumping together the accident rates of NYC bike messengers and Sun City retirees is going to create a combined rate that is not accurate for either group. Jay, that has nothing to do with your quip "Tom, statistically, you did not have any of your head injuries." Obviously, that's not what the statistics say. But unfortunately, there are plenty of people who seriously engage in your logical fallacy. One way it's been expressed is "Yes, there may be only one bike fatality per ten million miles ridden. BUT WHAT IF THAT ONE IS _YOU_??" What logical fallacy? The same one that leads millions of people to waste billions of dollars on lottery tickets. "It doesn't matter if the odds are hundreds of millions to one against me. What if _I_ win?" The same one that leads people to shun vaccinations for their kids. "The scientists have numbers claiming vaccinations don't cause autism, but what if they're wrong about _MY_ kid?" It's the belief that every individual is totally unique, and that large population data can say nothing about any person's chances of any occurrence. Who's on the other side of this debate? Medical science, for one - with large medicine trials that confirm that medicine A is beneficial; and with other trials that show that medicine B is no better than a placebo. They do this by testing large numbers of patients; and the assumption is that the next patient won't be miraculously different. He'll probably respond about the same way. Insurance companies are also on the side of statistics. They take in billions of dollars betting against the idea that everyone is absolutely unique. They know that there are individual differences; but they bet heavily on aggregate data. Of course some individuals fall far enough outside the norm to cost the insurance folks money; but the vast majority of their customers meet their predictions well enough to ensure healthy profits. Your statistics are so blunt, its like saying that a man has a one in 1,000 chance of getting ovarian cancer because that is the national statistic. Of course, you have to choose the applicable data for the proper cohort. (Although, weirdly enough, we're now in an age where gender is purportedly a matter of opinion!) And regarding large population studies: It's true that every large population has its probability distribution, usually a bell curve. And there are certainly individuals out on each tail end of each bell curve - the good end and the bad end. But that does not mean the studies say "little or nothing" about individual risks. Unless the individual is riding his bike off the roof of a skyscraper, his individual values are best thought of as modifications of the mean value. One individual will very likely be within two standard deviations of the mean. He's very unlikely to be more than three standard deviations away from the mean. Or in other words, almost everybody is almost average. My lifetime mileage is approaching 300,000 miles which is a multiple of standard deviations above the norm and yet you would put me in the same cohort as the once-a-year beach-bike cruiser at the local resort. Somewhere upthread, we were talking about your individual crashes or injuries, which you proclaimed to be many. Your lifetime mileage is extremely impressive. It would be interesting to take your personal injury count, divide by your lifetime mileage, and see how far you lie outside the available averages - recognizing that the "average" data is very rough. Frankly, what I'd expect is that you (and most other super-dedicated riders) would have much lower per-mile crash rates than average. FWIW, Forester claimed this in one of his books. But it depends. Danny MacAskill also has tons of mileage; but I'm sure he has tons of crashes. (He actually does ride his bike off rooftops.) And I've known avid riders who gave it up because they had too many crashes. Extreme risk takers and extremely clumsy people must be a big part of the "bad" tail of the bell curve. Above all, if a person chooses situations and behaviors that are well within his skills and capabilities, he can place himself further on the "good" side of that bell curve. If he takes excessive risks, he places himself further toward the "bad" side. An individual with a large number of crashes almost certainly didn't get those because statistics failed. It's because one way or other, his choices were bad. Thank god you're not a doctor -- you'd ignore family history, work exposure and every other relevant factor in predicting whether a particular patient was at risk for a specific disease. All the world is not the same, and everyone in the world is not exposed to the same risks. For example, most of the pedestrian deaths in Portland happened on a handful of roads. You are at risk crossing those roads -- more so than crossing any other roads in Portland. You're crazy to ignore the specific circumstances under which others ride, walk, sleep, garden, etc. I'm not ignoring them. But I'm saying almost everyone is almost average. That's true within any properly selected cohort. If someone's experience falls far outside the norm for his cohort, then something very strange is happening; or perhaps there's been some mis-measurement. Here's a specific example: The best data available (from several sources) estimates that there are about ten million miles ridden in the U.S. between bike deaths. (Actually more, but that round number will suffice.) And the best data I could find said about 45% of those were actually caused by TBI. Some others claim a higher TBI percentage, although the "75%" claim seems imaginary. So, again using very round numbers, there are probably at least 15 million miles ridden between bicycling TBI deaths. Yet I've recently read a claim "My helmets saved my life three times!" What's the most rational conclusion? Seems to me one possibility is that person is an ASTONISHINGLY bad rider, way out beyond the 99.9999th percentile. Or much more likely, that person is flat out wrong - that none of the three head impacts would have killed him, despite his heartfelt belief. IOW, I don't think the people who make that claim or very similar claims are really that far outside the norm. And - "Completely separate issue" warning! - I think it's still true that in most incidents when a bicyclist falls, he (or she) made a mistake. They could have avoided it if they had done things differently, including shunning a risk that was outside their capability at the moment. No wonder I feel weird I think I had 0.0000248 of a death on my ride just this morning: https://photius.com/rankings/2019/po...te_2019_0.html -- Andrew Muzi www.yellowjersey.org/ Open every day since 1 April, 1971 And that chart is a perfect example of statistical anomalies because the "low numbers of deaths" occur in rather unhealthy areas that the statistics do not have a good statistical reading on. And in general the high numbers of deaths per unit are in areas where there is a very large, dense and poor population in which medical care is almost non-existent. |
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#162
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On Wednesday, May 22, 2019 at 4:43:11 PM UTC-7, Frank Krygowski wrote:
On 5/22/2019 4:49 PM, jbeattie wrote: On Tuesday, May 21, 2019 at 2:07:39 PM UTC-7, Frank Krygowski wrote: On 5/21/2019 11:29 AM, jbeattie wrote: On Monday, May 20, 2019 at 4:10:56 PM UTC-7, Frank Krygowski wrote: On 5/20/2019 5:07 PM, jbeattie wrote: Tom, statistically, you did not have any of your head injuries. They were imagined... IOW: "Math is HARD!!!" It's not math. It's statistics -- where two plus two may equal four, depending on who you are. Large population studies say little or nothing about the risks encountered by individual cyclists in particular areas or engaging in specific types of cycling. Tom is an example -- as are most of my cohorts. It doesn't take a math genius to recognize that lumping together the accident rates of NYC bike messengers and Sun City retirees is going to create a combined rate that is not accurate for either group. Jay, that has nothing to do with your quip "Tom, statistically, you did not have any of your head injuries." Obviously, that's not what the statistics say. But unfortunately, there are plenty of people who seriously engage in your logical fallacy. One way it's been expressed is "Yes, there may be only one bike fatality per ten million miles ridden. BUT WHAT IF THAT ONE IS _YOU_??" What logical fallacy? The same one that leads millions of people to waste billions of dollars on lottery tickets. "It doesn't matter if the odds are hundreds of millions to one against me. What if _I_ win?" The same one that leads people to shun vaccinations for their kids. "The scientists have numbers claiming vaccinations don't cause autism, but what if they're wrong about _MY_ kid?" It's the belief that every individual is totally unique, and that large population data can say nothing about any person's chances of any occurrence. Who's on the other side of this debate? Medical science, for one - with large medicine trials that confirm that medicine A is beneficial; and with other trials that show that medicine B is no better than a placebo. They do this by testing large numbers of patients; and the assumption is that the next patient won't be miraculously different. He'll probably respond about the same way. Insurance companies are also on the side of statistics. They take in billions of dollars betting against the idea that everyone is absolutely unique. They know that there are individual differences; but they bet heavily on aggregate data. Of course some individuals fall far enough outside the norm to cost the insurance folks money; but the vast majority of their customers meet their predictions well enough to ensure healthy profits. Your statistics are so blunt, its like saying that a man has a one in 1,000 chance of getting ovarian cancer because that is the national statistic. Of course, you have to choose the applicable data for the proper cohort. (Although, weirdly enough, we're now in an age where gender is purportedly a matter of opinion!) And regarding large population studies: It's true that every large population has its probability distribution, usually a bell curve. And there are certainly individuals out on each tail end of each bell curve - the good end and the bad end. But that does not mean the studies say "little or nothing" about individual risks. Unless the individual is riding his bike off the roof of a skyscraper, his individual values are best thought of as modifications of the mean value. One individual will very likely be within two standard deviations of the mean. He's very unlikely to be more than three standard deviations away from the mean. Or in other words, almost everybody is almost average. My lifetime mileage is approaching 300,000 miles which is a multiple of standard deviations above the norm and yet you would put me in the same cohort as the once-a-year beach-bike cruiser at the local resort. Somewhere upthread, we were talking about your individual crashes or injuries, which you proclaimed to be many. Your lifetime mileage is extremely impressive. It would be interesting to take your personal injury count, divide by your lifetime mileage, and see how far you lie outside the available averages - recognizing that the "average" data is very rough. Frankly, what I'd expect is that you (and most other super-dedicated riders) would have much lower per-mile crash rates than average. FWIW, Forester claimed this in one of his books. But it depends. Danny MacAskill also has tons of mileage; but I'm sure he has tons of crashes. (He actually does ride his bike off rooftops.) And I've known avid riders who gave it up because they had too many crashes. Extreme risk takers and extremely clumsy people must be a big part of the "bad" tail of the bell curve. Above all, if a person chooses situations and behaviors that are well within his skills and capabilities, he can place himself further on the "good" side of that bell curve. If he takes excessive risks, he places himself further toward the "bad" side. An individual with a large number of crashes almost certainly didn't get those because statistics failed. It's because one way or other, his choices were bad. Thank god you're not a doctor -- you'd ignore family history, work exposure and every other relevant factor in predicting whether a particular patient was at risk for a specific disease. All the world is not the same, and everyone in the world is not exposed to the same risks. For example, most of the pedestrian deaths in Portland happened on a handful of roads. You are at risk crossing those roads -- more so than crossing any other roads in Portland. You're crazy to ignore the specific circumstances under which others ride, walk, sleep, garden, etc. I'm not ignoring them. But I'm saying almost everyone is almost average. That's true within any properly selected cohort. If someone's experience falls far outside the norm for his cohort, then something very strange is happening; or perhaps there's been some mis-measurement. Here's a specific example: The best data available (from several sources) estimates that there are about ten million miles ridden in the U.S. between bike deaths. (Actually more, but that round number will suffice.) And the best data I could find said about 45% of those were actually caused by TBI. Some others claim a higher TBI percentage, although the "75%" claim seems imaginary. So, again using very round numbers, there are probably at least 15 million miles ridden between bicycling TBI deaths. Yet I've recently read a claim "My helmets saved my life three times!" What's the most rational conclusion? Seems to me one possibility is that person is an ASTONISHINGLY bad rider, way out beyond the 99.9999th percentile. Or much more likely, that person is flat out wrong - that none of the three head impacts would have killed him, despite his heartfelt belief. IOW, I don't think the people who make that claim or very similar claims are really that far outside the norm. And - "Completely separate issue" warning! - I think it's still true that in most incidents when a bicyclist falls, he (or she) made a mistake. They could have avoided it if they had done things differently, including shunning a risk that was outside their capability at the moment.. -- - Frank Krygowski Drug trials are dramatically bad Frank. The numbers are vanishingly small on a statistical basis and because of this many trials show drugs that are actually effective doing worse that placebos. Claims of ice melting because of a rise of 2 degrees C above normal. Not mentioned that that was -40 degrees to -38 degrees. This had no effect whatsoever on ice. I have about the same as Jay and I have had crashes before but more now at age 75. I have had only a single collision with a car and it was at lower than 10 mph. I tossed away most of my records but I do remember 8 years of 10,000 miles each. At least two years of over 12,000 miles. I have been riding for 40 years. The wife and kids rode across the US twice. Once from Portland to Virginia Beach and once from here to I think Richmond Virginia for the Jr Nationals. |
#163
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On Friday, May 24, 2019 at 9:36:16 AM UTC-7, jbeattie wrote:
On Wednesday, May 22, 2019 at 4:43:11 PM UTC-7, Frank Krygowski wrote: On 5/22/2019 4:49 PM, jbeattie wrote: On Tuesday, May 21, 2019 at 2:07:39 PM UTC-7, Frank Krygowski wrote: On 5/21/2019 11:29 AM, jbeattie wrote: On Monday, May 20, 2019 at 4:10:56 PM UTC-7, Frank Krygowski wrote: On 5/20/2019 5:07 PM, jbeattie wrote: Tom, statistically, you did not have any of your head injuries. They were imagined... IOW: "Math is HARD!!!" It's not math. It's statistics -- where two plus two may equal four, depending on who you are. Large population studies say little or nothing about the risks encountered by individual cyclists in particular areas or engaging in specific types of cycling. Tom is an example -- as are most of my cohorts. It doesn't take a math genius to recognize that lumping together the accident rates of NYC bike messengers and Sun City retirees is going to create a combined rate that is not accurate for either group. Jay, that has nothing to do with your quip "Tom, statistically, you did not have any of your head injuries." Obviously, that's not what the statistics say. But unfortunately, there are plenty of people who seriously engage in your logical fallacy. One way it's been expressed is "Yes, there may be only one bike fatality per ten million miles ridden. BUT WHAT IF THAT ONE IS _YOU_??" What logical fallacy? The same one that leads millions of people to waste billions of dollars on lottery tickets. "It doesn't matter if the odds are hundreds of millions to one against me. What if _I_ win?" Ah, no. The whole point of my post is that unlike a lottery, the odds of wining or losing are different for each cyclist depending on a number of variables. Whether those odds are so high for a particular cyclist to create a psychological or practical barrier to cycling is a whole other matter. The same one that leads people to shun vaccinations for their kids. "The scientists have numbers claiming vaccinations don't cause autism, but what if they're wrong about _MY_ kid?" It's the belief that every individual is totally unique, and that large population data can say nothing about any person's chances of any occurrence. Who's on the other side of this debate? Medical science, for one - with large medicine trials that confirm that medicine A is beneficial; and with other trials that show that medicine B is no better than a placebo.. They do this by testing large numbers of patients; and the assumption is that the next patient won't be miraculously different. He'll probably respond about the same way. Insurance companies are also on the side of statistics. They take in billions of dollars betting against the idea that everyone is absolutely unique. They know that there are individual differences; but they bet heavily on aggregate data. Of course some individuals fall far enough outside the norm to cost the insurance folks money; but the vast majority of their customers meet their predictions well enough to ensure healthy profits. Both of these examples miss the point -- first, in large scale clinical trials, the cohort is carefully matched resulting in the approval of a drug for a very limited purpose (and a lot of off-label use for others). Health insurers simply eliminate coverage for pre-existing conditions, include annual maximums and re-insure large risks. They can use relatively blunt statistics and control risk in other ways. Accident policies may be denied to hang-glider users Your statistics are so blunt, its like saying that a man has a one in 1,000 chance of getting ovarian cancer because that is the national statistic. Of course, you have to choose the applicable data for the proper cohort.. (Although, weirdly enough, we're now in an age where gender is purportedly a matter of opinion!) And regarding large population studies: It's true that every large population has its probability distribution, usually a bell curve. And there are certainly individuals out on each tail end of each bell curve - the good end and the bad end. But that does not mean the studies say "little or nothing" about individual risks. Unless the individual is riding his bike off the roof of a skyscraper, his individual values are best thought of as modifications of the mean value. One individual will very likely be within two standard deviations of the mean. He's very unlikely to be more than three standard deviations away from the mean. Or in other words, almost everybody is almost average. My lifetime mileage is approaching 300,000 miles which is a multiple of standard deviations above the norm and yet you would put me in the same cohort as the once-a-year beach-bike cruiser at the local resort. Somewhere upthread, we were talking about your individual crashes or injuries, which you proclaimed to be many. It depends what you call "many." Compared to my MTB friends, it is few. Your lifetime mileage is extremely impressive. It would be interesting to take your personal injury count, divide by your lifetime mileage, and see how far you lie outside the available averages - recognizing that the "average" data is very rough. Frankly, what I'd expect is that you (and most other super-dedicated riders) would have much lower per-mile crash rates than average. FWIW, Forester claimed this in one of his books. Again, proving my simple point -- individuals have individual risk profiles. Mine is not the same as yours or Danny MacAskill's. But it depends. Danny MacAskill also has tons of mileage; but I'm sure he has tons of crashes. (He actually does ride his bike off rooftops.) And I've known avid riders who gave it up because they had too many crashes. Extreme risk takers and extremely clumsy people must be a big part of the "bad" tail of the bell curve. Above all, if a person chooses situations and behaviors that are well within his skills and capabilities, he can place himself further on the "good" side of that bell curve. If he takes excessive risks, he places himself further toward the "bad" side. An individual with a large number of crashes almost certainly didn't get those because statistics failed. It's because one way or other, his choices were bad. Thank god you're not a doctor -- you'd ignore family history, work exposure and every other relevant factor in predicting whether a particular patient was at risk for a specific disease. All the world is not the same, and everyone in the world is not exposed to the same risks. For example, most of the pedestrian deaths in Portland happened on a handful of roads. You are at risk crossing those roads -- more so than crossing any other roads in Portland. You're crazy to ignore the specific circumstances under which others ride, walk, sleep, garden, etc.. I'm not ignoring them. But I'm saying almost everyone is almost average.. That's true within any properly selected cohort. If someone's experience falls far outside the norm for his cohort, then something very strange is happening; or perhaps there's been some mis-measurement. Here's a specific example: The best data available (from several sources) estimates that there are about ten million miles ridden in the U.S. between bike deaths. (Actually more, but that round number will suffice.) And the best data I could find said about 45% of those were actually caused by TBI. Some others claim a higher TBI percentage, although the "75%" claim seems imaginary. So, again using very round numbers, there are probably at least 15 million miles ridden between bicycling TBI deaths. Yet I've recently read a claim "My helmets saved my life three times!" Fundamentally, this is all about helmets. No? And the crushing fear of MHLs. This is unfortunate because it turns the question of personal risk into a political discussion with statistics being used to prove a point. What's the most rational conclusion? Seems to me one possibility is that person is an ASTONISHINGLY bad rider, way out beyond the 99.9999th percentile. Or much more likely, that person is flat out wrong - that none of the three head impacts would have killed him, despite his heartfelt belief. IOW, I don't think the people who make that claim or very similar claims are really that far outside the norm. And - "Completely separate issue" warning! - I think it's still true that in most incidents when a bicyclist falls, he (or she) made a mistake. They could have avoided it if they had done things differently, including shunning a risk that was outside their capability at the moment. |
#164
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On Friday, May 24, 2019 at 3:36:33 PM UTC-7, Duane wrote:
Andre Jute wrote: On Friday, May 24, 2019 at 5:36:16 PM UTC+1, jbeattie wrote to Krygowski: Risk is different for different riders. If you JRA at 12mph on dry village streets, you are at low risk of injury. If you ride in snow, ice and rain on steep, broken roads, you are at a higher risk of injury. If you do laps in the Arc d'Triumph roundabout or filtering through London traffic, you're in a whole other risk category. And then, each of those categories is modified further by skill and experience. -- Jay Beattie. I've given up trying to educate that obstinate jerk, Frank Krygowski. But I must congratulate you on a good job, though your success will, like all past efforts, be temporary. Bad pennies keep turning up. You might add that, if you're on a road bike with narrow tyres, your risk of an incident is higher than if you're on balloons (50mm wide and up) though only if on downhills you proceed at the same pace as you would on narrow tyres rather than taking advantage of the greater capability of the balloons. Andre Jute 2.0 bar Jay is correct. Risk is different for different riders and even for the same rider in different circumstances. All cycling is not the same. Sometime I’m trudging through the traffic alone commuting to work.. Sometimes I’m out in the country in a group pushing it. Both have different parameters regarding risk etc. Some cyclists do only one or the other. Some do both. Hard to group them together statistically. And what would be the point anyway? -- duane You are perfectly correct in any case. If you are killed running a stop light it isn't pertinent to this discussion. If you are killed by a car running a stop light why weren't you more observant? I pulled up to where the San Mateo Bridge exists onto a city street. The light turned green and no one moved. 5 full seconds we sat there and this pickup truck went through the red light at 60 mph. Obviously the local people were well aware of that and always watched for it. In all the previous cases I had been there the exit light had stopped traffic piled up so that no one could run the light. |
#165
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On Friday, May 24, 2019 at 8:58:07 PM UTC-7, sms wrote:
On 5/24/2019 3:36 PM, Duane wrote: snip Jay is correct. Risk is different for different riders and even for the same rider in different circumstances. All cycling is not the same. Sometime I’m trudging through the traffic alone commuting to work. Sometimes I’m out in the country in a group pushing it. Both have different parameters regarding risk etc. Some cyclists do only one or the other. Some do both. Hard to group them together statistically. And what would be the point anyway? The point is that when the statistics don't support your premise you have to do something to justify your position. No one would think any worse of Frank if he used statistics honestly. Are you capable of using statistics properly? Hardly anyone is. I have had to use these things in engineering settings where PhD physicists with years of math and statistical analysis under their belt couldn't properly identify problems hidden in the statistics. Being able to see that and correct for it is how I remained at so many important positions. Even a slight problem - Tesla called to interview me for a job. I told them that I didn't think that they should call their feature an "autopilot". The man hung up on me in a huff. ANYONE should have been able to see the statistical relevance - any accident in which that "autopilot" was engaged automatically became the fault of Tesla. Therefore the insurance companies would tell their customers to always have it engaged. Tesla now call it a "navigation feature" and you are required to have both hands on the wheel when it is engaged. That sure was a difficult one to see coming. |
#166
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On Saturday, May 25, 2019 at 4:25:58 AM UTC-7, Duane wrote:
Andre Jute wrote: On Friday, May 24, 2019 at 11:36:33 PM UTC+1, Duane wrote: Andre Jute wrote: On Friday, May 24, 2019 at 5:36:16 PM UTC+1, jbeattie wrote to Krygowski: Risk is different for different riders. If you JRA at 12mph on dry village streets, you are at low risk of injury. If you ride in snow, ice and rain on steep, broken roads, you are at a higher risk of injury. If you do laps in the Arc d'Triumph roundabout or filtering through London traffic, you're in a whole other risk category. And then, each of those categories is modified further by skill and experience. -- Jay Beattie. I've given up trying to educate that obstinate jerk, Frank Krygowski. But I must congratulate you on a good job, though your success will, like all past efforts, be temporary. Bad pennies keep turning up. You might add that, if you're on a road bike with narrow tyres, your risk of an incident is higher than if you're on balloons (50mm wide and up) though only if on downhills you proceed at the same pace as you would on narrow tyres rather than taking advantage of the greater capability of the balloons. Andre Jute 2.0 bar Jay is correct. Risk is different for different riders and even for the same rider in different circumstances. All cycling is not the same. Sometime I’m trudging through the traffic alone commuting to work. Sometimes I’m out in the country in a group pushing it. Both have different parameters regarding risk etc. Some cyclists do only one or the other. Some do both. Hard to group them together statistically. And what would be the point anyway? -- duane I understand what you two are getting at, and I agree. But the actuary of an insurance company would be interested in the average danger in a representative year to all the cyclists in his demographic universe, simply as a base number from which to offset the factors we've already cited, plus no doubt others so that individual quotes can be prepared that will be different for me, riding in a country area and you, riding in a great metropolis. We've already had an example of where it has become difficult to get insurance for a mass ride of very occasional riders, where the cause might be insufficient data to make a rational quote, too many payouts for automobile crashes on that particular piece of road (from an insurance company's viewpoint not irrelevant at all), prior unprofitable experience insuring such mass bicycle rides, or simply common sense skepticism. You have to keep these two ideas, one based on demographics in large universes, one based on particular risks in particular places, separate, because the statistical principles applying to them are quite as different as the underlying assumptions of macro- and micro-economics.That is what's so tiresome about Krygowski's ignorant insistence that all you need is a technician's rote-learned math and Leontiev is your uncle: hey, presto, you understand statistics! This ignorance and insensitivity to people, coupled to immorality, is what drives Krygowski's repeated attempts to argue from the particular (that what he himself does is superior to what anyone else does) to the general, and then to assume that 200 or 300 unnecessarily dead cyclists every year don't matter. Andre Jute Actuaries rule Well statistics in the macro sense can serve to direct solutions to macro problems but don’t serve much use on the micro level. I think I was taught that in a first year stats course. But I think that’s what you just said. -- duane Injuries to cyclists and damage to their equipment is so rare that it is normally covered under your home and auto insurance without question. |
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On Wednesday, May 29, 2019 at 9:15:16 PM UTC+1, Tom Kunich wrote:
Injuries to cyclists and damage to their equipment is so rare that it is normally covered under your home and auto insurance without question. Exactly. It's the same problem you've covered several times in this thread: Not enough data, universe too small or uneconomic for specific purpose-directed research, etc. Result: actuaries lump the cost in with something else with better numbers. That leaves the field wide open for erroneous interpretations of the data. It is also the reason we talk about bicycling fatalities more than their number really justifies (at least in Krygowski's cramped view of the value of human life), that deaths are at least particularised hard numbers, certified by the Census Bureau or the bureaucracy of a large city, in a recurring case on this newsgroup New York. There aren't all that many legitimate alternative sources. Andre Jute Frustration with inadequate data is part of any decision-making job description -- Peter Drucker |
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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.
On 5/29/2019 4:58 PM, Andre Jute wrote:
On Wednesday, May 29, 2019 at 9:15:16 PM UTC+1, Tom Kunich wrote: Injuries to cyclists and damage to their equipment is so rare that it is normally covered under your home and auto insurance without question. Exactly. It's the same problem you've covered several times in this thread: Not enough data, universe too small or uneconomic for specific purpose-directed research, etc. Result: actuaries lump the cost in with something else with better numbers. That leaves the field wide open for erroneous interpretations of the data. It is also the reason we talk about bicycling fatalities more than their number really justifies (at least in Krygowski's cramped view of the value of human life), that deaths are at least particularised hard numbers, certified by the Census Bureau or the bureaucracy of a large city, in a recurring case on this newsgroup New York. There aren't all that many legitimate alternative sources. Andre Jute Frustration with inadequate data is part of any decision-making job description -- Peter Drucker thanks for that I never tire of Druckerisms. -- Andrew Muzi www.yellowjersey.org/ Open every day since 1 April, 1971 |
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Cycling is dangerous | Garry Jones | General | 375 | November 21st 03 05:52 PM |