Data collection

[brookeansley]

Hi!

I'm a graduate student at the University of Georgia and I am conducting a research project on the effects that height, weight, shoe size, and age have on rowing performance. I have created this questionnaire to collect data. I need 50 observations at a minimum so will appreciate any responses provided! Thank you in advance.

https://forms.gle/spLi9xWNT13sqRFc8

[Dangerscouse]

Done

[MPx]

Me too...

One observation - it asks for 500 and 2k PRs - easy enough to enter. But in my case I did them 13 years ago so can't really correlate vs age.

[Sakly]

Done.
Had I filled this form a year ago, the results would deviate much

[rleeden]

Done

Another observation, is you ask for shoe size, but you don't specify which sizing system. I am size 10 (UK), 11 (US) or 45 (EU), and I believe there are further systems for Japan and Australia and probably others.

[Sakly]

Done

Another observation, is you ask for shoe size, but you don't specify which sizing system. I am size 10 (UK), 11 (US) or 45 (EU), and I believe there are further systems for Japan and Australia and probably others.

Because of this I added "Eur" to my number, observed the same.

[p_b82]

Isn't it missing a very important metric of training volume?

I mean with respect, you will find that typically the bigger/heavier a person is, the generally larger shoe size. Numerous studies have already proved that long leavers generally equate to good erg performances. (with a lot of the assumptions ruled out scientifically)

But by not including the training volume a person does (with a bias towards exercise that benefits rowing) you're not actually able to compare apples to apples imo.
A 7' monster who sits on the couch all day who's never sat on an erg will very likely give much poorer and lower figures than some-one 5' who trains appropriately every day. And the focus on 500m & 2k as performance markers will trend towards the bigger/stronger athlete vs the more aerobically fit who can manage 5k and upwards better.

Apologies, a bit of a tangent to the request, but part of my job falls into meaningful dataset analysis; and one of the things that is always important to avoid is falling into a bias confirmation trap. Also avoid datasets that don't provide specific enough datapoints to draw conclusions that aren't general ones.