Car Repair vs Bike Repair

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In article <[email protected]>,
Tom Compton <[email protected]> wrote:

> Average mileage for a bicycle tire is 724 miles, a car tire, 40,000. At \$40 per bike tire and \$50
> per car tire its 2 x \$40 / 724 = \$.11 per mile to ride a bike and 4 x \$50 /40000 = \$.005 per mile
> to drive or 22 times more expensive (for tires) to ride than to drive.

Huh. I have got Conti Ultra 2000 700 x 28 on a couple of bikes, getting 2500 to 3000 miles on the
rear and at least three times that on the front (hasn't worn out yet). I paid \$24 per tire- just
basing on the rear tire at 2500 miles, that's \$.0104 per mile.

Tim McNamara <[email protected]> wrote:
: Mean 1746. Mile Variance 4194162. Standard Deviation 2048. Mile Sample Range 12753. Confidence
: Interval for Sample Mean { 1370., 2123.}
:
: These results look kinda hinkey (e.g., standard deviation > mean) based on my grad school stats
: class umpteen years ago. Also there's no number of samples (n), etc.

sample size is 116 (it's at the bottom). if you look at the histogram the standard deviation makes
more sense. if one standard deviation is to account for around 68% of the data 2048 would be
ballpark correct. most of the data is on either side (200 miles and 1750, 2750, or >3500). that the
standard dviation is so high just means the data is spread out (this ain't no bell curve, more like
an inverted bell).
--
david reuteler [email protected]

In article <[email protected]>, David Reuteler
<[email protected]> wrote:

> Tim McNamara <[email protected]> wrote:
> : Mean 1746. Mile Variance 4194162. Standard Deviation 2048. Mile Sample Range 12753. Confidence
> : Interval for Sample Mean { 1370., 2123.}
> :
> : These results look kinda hinkey (e.g., standard deviation > mean) based on my grad school stats
> : class umpteen years ago. Also there's no number of samples (n), etc.
>
> sample size is 116 (it's at the bottom). if you look at the histogram the standard deviation makes
> more sense. if one standard deviation is to account for around 68% of the data 2048 would be
> ballpark correct. most of the data is on either side (200 miles and 1750, 2750, or >3500). that
> the standard dviation is so high just means the data is spread out (this ain't no bell curve, more
> like an inverted bell).

Yah, I think there's some clearly "junk" data points which is probably screwing up the stats.
There's an awful lot of tires listed as "worn out" after only 200 miles which seems just silly for
anything other than Conti Supersonics. "Worn out" may have different meanings for different
contributors. I consider a tire "worn out" when I can see casing cords showing through the tread;
others consider them "worn out" when the rear tire squares off a bit.

Tim McNamara <[email protected]> wrote:
: Yah, I think there's some clearly "junk" data points which is probably screwing up the stats.
: There's an awful lot of tires listed as "worn out" after only 200 miles which seems just silly for
: anything other than Conti Supersonics. "Worn out" may have different meanings for different
: contributors. I consider a tire "worn out" when I can see casing cords showing through the tread;
: others consider them "worn out" when the rear tire squares off a bit.

yea, that's right. 30 of 116 people wore their tires out in 200 miles or less (5 in 50 or less).

as an aside, looking at the data again i'm thinking that each "mishap" does not necessarily end the
life of the tire making my earlier note that most tires don't last long enuf to wear out incorrect.

check here for their analysis

http://www.analyticcycling.com/TiresReport072502.html

which is interesting 'cause they imply that each mishap does end the life of the tire ("Tires often
die from mishaps long before they ware(sic) out. Only getting a few hundred miles from a tire is
common." see second graph, "What is the frequency distribution of mileage between mishaps for all
tires?"). i don't understand how they can make that claim when the input they used to get the data
makes no note of whether the mishap ended the tire's life.

check here for the input page

http://www.analyticcycling.com/TiresMishapData_Page.html

if you wanna see something funky click reset and then "blowout" for the type of mishap. it'll come
back with a mean of 4170 miles and a standard deviation of 27272. there are two data points >3500
and they must be way over.
--
david reuteler [email protected]

I also think it's funny that the first thing we do before going for a ride (2-3 times a week) is
check the air pressure, and pump it up to the exact PSI of the tire. Yet... we'll get in our car
with our whole family and check the air pressure in those tires maybe once a year. What the hell is
wrong with us??? lol

Kraig Willett wrote:

> I serviced the brakes of my truck today:
>
> Two new rotors: \$70 Two sets of brake pads: \$20
>
> So, this works out to be \$45 per assembly.
>
> If I owned a disc brake equipped mountain bike, the same job would have cost me:
>
> One new rotor: \$25 Brake Pads: \$20
>
> for a total of \$45 for the assembly.
>
> Is it just me, or, does anyone else find this amusing?
>
> --
> ==================
> Kraig Willett www.biketechreview.com
> ==================

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