Fatty Masters Results

"Phil Holman" <piholmanc@yourservice> wrote in message
news:[email hidden]...

Quoted message said:

Weight(lb) Max=216, min=129, mean=167, sd=21.35
Height(in) Max=75, min=66, mean=70.65, sd=2.78

I did omit one outlier from the data. Comparing these stats to the
general population, they are in the 25th to 30th percentile of weight
and not statistically different in height. A best fit regression of
weight versus height came up with weight = .0714height^1.82 (r=.57) and
weight = -154.28+4.5473height (r=.59). Omitting the data point with the
largest residual resulted in weight =.0016height^2.7 (r=.73).

Uhh, Phil, can you put that in English?

It appears that rbr masters are typically closer to ideal weight that the
general population?

"Tom Kunich" <cyclintom@yahoo. com> wrote in message
news:[email hidden]...

Quoted message said:

"Phil Holman" <piholmanc@yourservice> wrote in message
news:[email hidden]...

Quoted message said:

Weight(lb) Max=216, min=129, mean=167, sd=21.35
Height(in) Max=75, min=66, mean=70.65, sd=2.78

I did omit one outlier from the data. Comparing these stats to the
general population, they are in the 25th to 30th percentile of weight
and not statistically different in height. A best fit regression of
weight versus height came up with weight = .0714height^1.82 (r=.57)
and
weight = -154.28+4.5473height (r=.59). Omitting the data point with
the
largest residual resulted in weight =.0016height^2.7 (r=.73).

Uhh, Phil, can you put that in English?

It appears that rbr masters are typically closer to ideal weight that
the general population?

Yes, it's about the 25th percentile of the general population.

What the data says is that the sample is at ideal weight which is not
overly due to any height factor, i.e. a short sample (sample height is
very representative of the spread in the general population). One would
expect weight (volume) to increase roughly with the cube of height
(length) change. It was close to this when I removed one of the data
points. Weight is only moderately correlated with height (r = .57) for
this sample. This means that only 32% (.57^2) of variation in weight is
explained by variation in height.

Try this equation on yourself to see how well it predicts your weight.
weight =.0016*height^2.7

If I input my own height of 74 inches, my weight comes out to
..0016*74^2.7 = 178 lb which is fairly close.

Phil H

in message <[email hidden]>, Phil Holman

('piholmanc@yourservice') said:

I'm 10 open category riders short of conducting this test, however, here
are the stats on the volunteers who did submit their data.

Weight(lb) Max=216, min=129, mean=167, sd=21.35
Height(in) Max=75, min=66, mean=70.65, sd=2.78

I did omit one outlier from the data. Comparing these stats to the
general population, they are in the 25th to 30th percentile of weight
and not statistically different in height. A best fit regression of
weight versus height came up with weight = .0714height^1.82 (r=.57) and
weight = -154.28+4.5473height (r=.59). Omitting the data point with the
largest residual resulted in weight =.0016height^2.7 (r=.73).

Ah! So even among the masters fattie I am a master relatively fatty. This
gives me great comfort.

--
[email hidden] (Simon Brooke) http://www.jasmine.org.uk/~simon/

Morning had broken, and there was nothing we could do but wait
patiently for the RAC to arrive.

Phil Holman' piholmanc@yourservice said:

"Tom Kunich" <cyclintom@yahoo. com> wrote in messagenews:[email hidden]...

Quoted message said:

"Phil Holman" <piholmanc@yourservice> wrote in message
news:[email hidden]...

Quoted message said:

Weight(lb) Max=216, min=129, mean=167, sd=21.35
Height(in) Max=75, min=66, mean=70.65, sd=2.78

Quoted message said:

Quoted message said:

I did omit one outlier from the data. Comparing these stats to the
general population, they are in the 25th to 30th percentile of weight
and not statistically different in height. A best fit regression of
weight versus height came up with weight = .0714height^1.82 (r=.57)
and
weight = -154.28+4.5473height (r=.59). Omitting the data point with
the
largest residual resulted in weight =.0016height^2.7 (r=.73).

Quoted message said:

Uhh, Phil, can you put that in English?

Quoted message said:

It appears that rbr masters are typically closer to ideal weight that
the general population?

Yes, it's about the 25th percentile of the general population.

What the data says is that the sample is at ideal weight which is not
overly due to any height factor, i.e. a short sample (sample height is
very representative of the spread in the general population). One would
expect weight (volume) to increase roughly with the cube of height
(length) change. It was close to this when I removed one of the data
points. Weight is only moderately correlated with height (r = .57) for
this sample. This means that only 32% (.57^2) of variation in weight is
explained by variation in height.

Try this equation on yourself to see how well it predicts your weight.
weight =.0016*height^2.7

If I input my own height of 74 inches, my weight comes out to
.0016*74^2.7 = 178 lb which is fairly close.

That's pretty surprising - I'm about 76 inches now at 62 years old and
my present weight as if this morning is 196.6 lbs. I usually put on a
little weight over the winter and take it off over the summer only to
put it back on after October. Your formula give 191 as my ideal weight
though when I'm riding I've discovered that I can climb like a snail
at my present weight and like an angel after I hit 188.