On Oct 6, Willem <
wil...@turtle.stack.nl> wrote:
> ) You've entered a road race. It's around a loop, a lakeside
> ) race, but very long, like a marathon.
> )
> ) It contains a large field of competitors, including Median
> ) Mel, who's the median speed runner. And Al Average,
> ) who runs at the average speed of the entire field.
> )
> ) After a while, you get bored, so you start to count the
> ) runners whom you pass, and the runners whom pass
> ) you. You notice something funny: the number who pass
> ) you equals the number you pass, on average, per hour.
> )
> ) How fast are you, relative to Al or Mel?
>
> Assuming that this is hell, where you have to run endlessly (or at least
> long enough to have, or be, passed by everyone a lot of times),
Right. That's why I stipulated "after while, you start
counting...".
Then we can assume the runners, and speeds, are uniformly
distributed around the circuit ('completely random'), a key
assumption. So you pass/are passed by a representative sample
of the field, no matter where or when.
> and also that everybody runs at a constant speed, then your speed
> should be the same as that of Average Al.
>
> Sketch of proof: The number of times that a given person passes (or is
> passed by) you in a given period is a linear function of their speed
> difference to you. (Negative numbers meaning that you pass them.)
> So if the average of those passes is 0, the average of speed differences
> must also be 0, and your speed must be the average speed.
>
> Suppose the track is 1km long, then someone running 1km/h faster will
> pass you 1 time per hour, and someone running 3km/h slower will be
> passed by you 3 times an hour.
Another way to see it, is to subtract the average speed
from everyone's speed. Which simplifies the problem,
but doesn't change the relative speeds or positions.
Now let's try another: You perform a random telephone
survey of local residents, to estimate population body
weights. You notice that the number who weigh more
than you, equals the number who weigh less, no matter
how many you call. What can you infer about your weight,
relative to the mean and median?
Why is this case different, given that in both problems,
you sample from a uniformly distributed population?
--
Rich