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.