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HOW DANGEROUS IS CYCLING? DEPENDS ON WHICH NUMBERS YOU EMPHASISE.



 
 
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  #161  
Old May 29th 19, 08:57 PM posted to rec.bicycles.tech
Tom Kunich[_5_]
external usenet poster
 
Posts: 169
Default 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  
Old May 29th 19, 08:57 PM posted to rec.bicycles.tech
Tom Kunich[_5_]
external usenet poster
 
Posts: 169
Default 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  
Old May 29th 19, 08:59 PM posted to rec.bicycles.tech
Tom Kunich[_5_]
external usenet poster
 
Posts: 169
Default 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  
Old May 29th 19, 09:04 PM posted to rec.bicycles.tech
Tom Kunich[_5_]
external usenet poster
 
Posts: 169
Default 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  
Old May 29th 19, 09:13 PM posted to rec.bicycles.tech
Tom Kunich[_5_]
external usenet poster
 
Posts: 169
Default 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  
Old May 29th 19, 09:15 PM posted to rec.bicycles.tech
Tom Kunich[_5_]
external usenet poster
 
Posts: 169
Default 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.
  #167  
Old May 29th 19, 10:58 PM posted to rec.bicycles.tech
Andre Jute[_2_]
external usenet poster
 
Posts: 9,086
Default 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
  #168  
Old May 29th 19, 11:06 PM posted to rec.bicycles.tech
AMuzi
external usenet poster
 
Posts: 10,334
Default 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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