19sawickin wrote:Can anyone tell me what I'm supposed to do for "different ways to approach hypothesis" in the "applications" section? The scioly page gives an example of testing a parachute with varying masses I believe, and said that using a computer simulation is an example of approaching the hypothesis from a different angle. I've used this idea at a few invitationals as well as state tournaments, and it has never been a problem. However, at the Cornell invitational, my team received 2's in everything, and a 0 for this section, and no explanation was provided. We performed an experiment to determine the relationship between the volume of water in a constant sized beaker, and the amount of time it took for a drop of dye to reach the bottom of the beaker. In my questioned area, I more or less said that a different way to approach our hypothesis would be to use a computer simulation to take into account the surface tension of water as well as the dye, and provide more constant conditions. I literally said "a different way to approach our hypothesis is to..." so it was definitely present, meaning my example must not have been valid? What could I have done instead?
Although this is a bit late, I feel like I'll feel better receiving an answer to a question if I answer one.
From reading what you put in your experiment, it seems to me as though that would be an improvement you have, or "suggestions for improvement of specific experiment given." I think the proctors are looking for a different experiment, but not necessarily completely different. An example of this would be to change your medium to a more viscous liquid to see if the trend of volume of liquid still applies. Hope this helped
Soooo my question:
It seems to me as though statistics don't really make any sense in experimental design. While the mean, median, mode, range, and line of best fit are all represented through the trials, I don't understand how you can use other measures of variation. Like someone said before, the easiest experiments to do are ones in which both the IV and DV are correlated and infinitely adjustable, so I wouldn't see the benefits of including a histograph or frequency table. Unless I'm just really slow at competitions, generally only 3 trials of 3 IVs are done, and if I remember correctly standard deviation needs at least 5 data points, as does IQR. Is it worth it to do 2 extra trials for each of the three levels of the independent variable just to get more statistics? Thanks!!!
For example, at one invitational, the topic was sound, so we tested different materials to determine the different sounds. It was just a simple experiment, so we had enough time to do 4 trials. My motto for Exp Des is "Keep it simple, stupid!" (Not saying that you are stupid - you're in SO!) Hope this helps!