Experimental Design B/C
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Re: Experimental Design B/C
Obviously you need to split up a team. If you don't know that by know you shouldn't be doing this event. Common sense, people. Also, don't get DQ'd. Don't do anything that might get you DQ'd. Also common sense.
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Re: Experimental Design B/C
you forgot something... answer the question -- test within the topic... we hosted a dual meet with us and another school, and out of the 4 teams not a single one did an experiment under the topic. (which was surface tension)
if you don't stay on topic.... whew. youre in trouble!!!
if you don't stay on topic.... whew. youre in trouble!!!

No matter what the experiment's result, there will always be someone eager to:(a) misinterpret it(b) fake it, or (c) believe it supports his own pet theory.
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Re: Experimental Design B/C
Of course, you should always make sure you're running an experiment that falls under the topic. But more importantly, be sure to jot down in your write-up how your experiment relates to the topic, preferably more than once. Even if it seems to be a questionable experiment, if you can make a solid link between your experiment and the topic, it should push you over the edge to having a valid experiment.
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Re: Experimental Design B/C
I have a bunch of questions about the rubric this year:
1. What does it mean when we have to "operationally define the IV and DV"
2. How should "example calculations" be done? Last year it was supposed to be done on the statistics page, but this year it says under data table?
3. For statistics, could someone give me examples/clarifications of central tendency (standard deviation?), variation, regression analysis (line of best fit? what if your data isn't applicable?), and another appropriate statistic?
4. And finally, for applications/recommendations, can someone explain what a "suggestion for other ways to look at hypothesis given." is?
Thanks!
1. What does it mean when we have to "operationally define the IV and DV"
2. How should "example calculations" be done? Last year it was supposed to be done on the statistics page, but this year it says under data table?
3. For statistics, could someone give me examples/clarifications of central tendency (standard deviation?), variation, regression analysis (line of best fit? what if your data isn't applicable?), and another appropriate statistic?
4. And finally, for applications/recommendations, can someone explain what a "suggestion for other ways to look at hypothesis given." is?
Thanks!
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Re: Experimental Design B/C
IMHO, since how one does an ED is very particular and personal.
1. It means to give an explicit definition of each. For instance, in an experiment that involves dropping a ball, the IV might be "the height of release" and you'd operationally define that as "the shortest distance, measured with a ruler in centimeters, between the bottommost point of the ball and the floor" and the DV might be "the time to fall" and you'd operationally define that as "the time elapsed, measured in seconds with a stopwatch, between the instant ball is released by the fingers and is allowed to fall under its own gravity and the instant the ball first makes contact with the floor." Precise description of the value to be recorded, the instrument that will be used, and the units used to measure it are the key facets.
2. Where example calcs are done on your writeup is irrelevant - that's just for the rubric's efficiency. Do your calculations wherever you like. Write out the formulas, and then pick a level of your IV and show the calculation of that statistic. For instance, for your Standard Deviation, write out the formula, then fill in the calculation with the values from one of your tests.
3. Central tendency should be mean (conceivably median), variation should be standard deviation, regression should be an LSRL (if your data isn't applicable to a regression line, then you probably picked a bad experiment), and the other appropriate statistic can be whatever you like. It can involve hypothesis testing (p-values), r and Rsquared values, Coefficient of Variation... anything you like. It's good to label each of your statistics with the category you'd like them to be graded on (ie: write "Measure of Central Tendency: Mean" next to your table of level means).
4. That one was always the fuzziest. A natural interpretation would be "given this hypothesis, what's one other way we could test it?" Another option is "analyze your hypothesis critically and come up with some other things it might imply, and look for "other things it might say." I wish I could give a better answer for this one - it's weird!
1. It means to give an explicit definition of each. For instance, in an experiment that involves dropping a ball, the IV might be "the height of release" and you'd operationally define that as "the shortest distance, measured with a ruler in centimeters, between the bottommost point of the ball and the floor" and the DV might be "the time to fall" and you'd operationally define that as "the time elapsed, measured in seconds with a stopwatch, between the instant ball is released by the fingers and is allowed to fall under its own gravity and the instant the ball first makes contact with the floor." Precise description of the value to be recorded, the instrument that will be used, and the units used to measure it are the key facets.
2. Where example calcs are done on your writeup is irrelevant - that's just for the rubric's efficiency. Do your calculations wherever you like. Write out the formulas, and then pick a level of your IV and show the calculation of that statistic. For instance, for your Standard Deviation, write out the formula, then fill in the calculation with the values from one of your tests.
3. Central tendency should be mean (conceivably median), variation should be standard deviation, regression should be an LSRL (if your data isn't applicable to a regression line, then you probably picked a bad experiment), and the other appropriate statistic can be whatever you like. It can involve hypothesis testing (p-values), r and Rsquared values, Coefficient of Variation... anything you like. It's good to label each of your statistics with the category you'd like them to be graded on (ie: write "Measure of Central Tendency: Mean" next to your table of level means).
4. That one was always the fuzziest. A natural interpretation would be "given this hypothesis, what's one other way we could test it?" Another option is "analyze your hypothesis critically and come up with some other things it might imply, and look for "other things it might say." I wish I could give a better answer for this one - it's weird!
Harriton '10, UVA '14
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Re: Experimental Design B/C
so would doing many repeated experiments help?
and also would choosing many different materials with which to do these experiments help? To be prepared for this event?
and also would choosing many different materials with which to do these experiments help? To be prepared for this event?
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Re: Experimental Design B/C
Try to do the same experiment with different materials each time you practice [that experiment]. For instance, a ramp made out of a plank of wood and coins one time, and a clipboard and weights the next time, etc.
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Re: Experimental Design B/C
Hey guys, I was wondering, for the 2011 rubric for Exp. Des. is it the same every year? Or does it change. Because, we're making pop-quizzes for our team, but we're not sure if we should use that rubric or not. Thanks!
It's so easy, even a Badger could do it.
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Re: Experimental Design B/C
It normally is the same each year, but it's always good to double check.
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