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Re: Experimental Design B/C

Posted: November 9th, 2015, 6:46 am
by brayden box
Could you do 4 levels? And if you did, would you get more points for it?

Re: Experimental Design B/C

Posted: November 9th, 2015, 7:12 am
by samlan16
brayden box wrote:Could you do 4 levels? And if you did, would you get more points for it?
You can, but they only care about the first three that you list under the IV. So no, you would not get more points.

In case you have similar questions in the future, check the rubric here before asking.

Re: Experimental Design B/C

Posted: November 10th, 2015, 8:36 am
by Whiteheat073
Is there going to be Experimental Design in regionals for Div. B?

Re: Experimental Design B/C

Posted: November 10th, 2015, 12:00 pm
by samlan16
Whiteheat073 wrote:Is there going to be Experimental Design in regionals for Div. B?
I don't know the conventions for your regional tournament, but given that you are in Illinois, it should be run. Their state organization is well established, so you should expect all events to be run.

Re: Experimental Design B/C

Posted: November 15th, 2015, 10:28 am
by Willows
Have you guys ever used anything other than linear regression in an experiment? Do you think it'd be worth it to know quadratic, logarithmic, and/or sinusoidal regressions? And if a quadratic curve does fit the data better, should it still be sketched on the graph as a "line (or curve) of best fit"?

Re: Experimental Design B/C

Posted: November 15th, 2015, 10:33 am
by laneyoung
Whiteheat073 wrote:Is there going to be Experimental Design in regionals for Div. B?
While this isn't an official answer, Experimental Design should be run at the regional you're attending (assuming that your school is Wredling).

Re: Experimental Design B/C

Posted: November 22nd, 2015, 8:49 pm
by watermydoing14
Willows wrote:Have you guys ever used anything other than linear regression in an experiment? Do you think it'd be worth it to know quadratic, logarithmic, and/or sinusoidal regressions? And if a quadratic curve does fit the data better, should it still be sketched on the graph as a "line (or curve) of best fit"?
I think it's generally best to use a linear regression because then you can interpret the intercepts. Plus, I think it's generally good practice to linearize data when the relationship turns out not to be linear (although I don't know that the event supervisors would expect teams to do that in the time given). Best case scenario is that you design an experiment that you know will turn out to be linear. If it's not, I would still sketch the line/curve of best fit just to be safe. Although technically you don't /need/ it since it's in the statistics section, so as long as you have enough other appropriate statistics to get the 6 points, you should be fine. However, I'm not sure how relevant other statistics would be on a non-linear graph, so I think having a non-linear graph could be a bit of a risk.

Re: Experimental Design B/C

Posted: November 28th, 2015, 4:00 pm
by coprolite_dipstick
Hi, what exactly are linear/quadratic/logarithmic/sinusoidal regressions? This is my first year doing the event and I've honestly never even heard of those before.

Also, I'm in Div. B, so would knowing those be necessary for my division or is it mostly just for C?

Thanks

Re: Experimental Design B/C

Posted: November 29th, 2015, 2:57 pm
by samlan16
coprolite_dipstick wrote:Hi, what exactly are linear/quadratic/logarithmic/sinusoidal regressions? This is my first year doing the event and I've honestly never even heard of those before.

Also, I'm in Div. B, so would knowing those be necessary for my division or is it mostly just for C?

Thanks
In simple terms, a regression is a statistical model of a set of bivariable data (i.e. has an independent and dependent variable, each with some numerical value) such that the average distance from the line to each point is a minimum. This link talks about linear regressions, which should be used when the data appears to form a uniform line. Likewise, quadratic regressions are for data that form a parabolic shape; logarithmic regressions for data forming the shape of a logarithmic graph; and sinusoidal regressions for data forming the shape of a sine wave. The derivation involves a ton of linear algebra; if you want to look it up, feel free.

Regressions are not required for either division and do not earn you brownie points, but you definitely will impress the judges if you do a regression.

Re: Experimental Design B/C

Posted: December 9th, 2015, 9:55 am
by Bozongle
I've been in Experimental Design for a few years now and the same question still comes to mind: When getting to a very competitive level (i.e. the teams competing know the rubric inside and outside, word for word in their head), for example, top 10 at Nationals, how are teams distinguished in rank? When it gets to a point where each Ex Des has the same key information required, how does a proctor decide if between four 120 point Ex Des's, one should be the champion?

Considering Experimental Design is mostly memorization of the rubric with consistent practice, I'm wondering what kind of special flair a team should do to distinguish themselves from the rest of the high-scoring pack.