Experimental Design B/C

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illusionofconfusion
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Re: Experimental Design B/C

Post by illusionofconfusion » November 7th, 2014, 12:25 pm

Does anyone have a good way to distinguish between what goes in the conclusion and what goes in the analysis? Most of the time it seems to me like they're the same. :?
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Re: Experimental Design B/C

Post by Panda Weasley » November 7th, 2014, 1:32 pm

The Analysis is a summery of what happened during the test. You are basically summarizing your results and discussing the data points. If there are any unusual data points or trends you noticed this is where you would write about them. You DO NOT discuss your hypothesis here!
The Conclusion is whether your hypothesis was supported or unsupported based on your data, and explaining why.

They do seem pretty similar, when I first started I was very confused by it. I don't really have a good method of remembering which is which though. Something that does help me though is the Analysis is analyzing the data while the Conclusion is concluding the report. Does that help at all? Maybe someone else here will have a better method.
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Re: Experimental Design B/C

Post by XJcwolfyX » November 7th, 2014, 2:33 pm

Analysis:
Say all of your data. You have to mention every data point, including your averages. Then, discuss unusual data points. Make sure you're specific...such as "The time of 2.67 seconds in the 20 cm tall ramp height data was an unusual data point..." and then explain it: "...this could have been caused by...X, Y, Z." If there are no unusual data points, say that. Do not emit that from your analysis. Then, discuss the trends. "As the ramp height increased, the amount of time it took the ball to roll down it and across the floor 1 meter decreased." Then, support this with data. "This is shown because the average times for ramp heights 10 cm, 20 cm, and 30 cm were 2.90, 2.63, and 2.11, respectively. Clearly, these numbers are increasing."

Conclusion:
For your conclusion, you restate and evaluate your hypothesis. "Our hypothesis that said ________ (restate the whole thing here) was correct/incorrect (choose one). This is shown in the data because the average for the 10 cm, 20 cm, and 30 cm ramps were X, Y, Z respectively (yes, you just said this above), which shows a clear increase/decrease in time." Then, you should give a reason why this happened. "This is most likely because (scientific explanation here, such as "as you increase the ramp height, the ball begins with more potential energy and therefore has more kinetic energy when it comes to the bottom of the ramp")......

Hope this helped.
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Re: Experimental Design B/C

Post by illusionofconfusion » November 8th, 2014, 12:06 pm

Okay, that really helps! I had noticed that I was writing almost the same thing for both, and I was confused, but now I'm not! :D
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Re: Experimental Design B/C

Post by CulturallyScientific » November 16th, 2014, 10:59 pm

Has anyone thought of including "analyze quantitative data with statistical tools, such as T-Test, Chi-Square test, etc" in the recommendations? I only relatively recently learned more about statistics and ExCel, so just wondering if this crossed anyone else's mind.
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Re: Experimental Design B/C

Post by samlan16 » November 29th, 2014, 8:59 am

CulturallyScientific wrote:Has anyone thought of including "analyze quantitative data with statistical tools, such as T-Test, Chi-Square test, etc" in the recommendations? I only relatively recently learned more about statistics and ExCel, so just wondering if this crossed anyone else's mind.
My partner and I kind of did this last year being overzealous about taking AP Stats, but (at least in GA) it gives you no advantage because they want to see how you would adjust the experiment if you had no time or material constraints. If you really want to, you can do an inferential stat in the actual stats section (but once again, no advantage to it because you can simply do standard deviation).
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Re: Experimental Design B/C

Post by CulturallyScientific » November 29th, 2014, 10:34 am

samlan16 wrote:
CulturallyScientific wrote:Has anyone thought of including "analyze quantitative data with statistical tools, such as T-Test, Chi-Square test, etc" in the recommendations? I only relatively recently learned more about statistics and ExCel, so just wondering if this crossed anyone else's mind.
My partner and I kind of did this last year being overzealous about taking AP Stats, but (at least in GA) it gives you no advantage because they want to see how you would adjust the experiment if you had no time or material constraints. If you really want to, you can do an inferential stat in the actual stats section (but once again, no advantage to it because you can simply do standard deviation).
Oh, okay. We'll just stick to standard deviation then. Thanks salman16!
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Re: Experimental Design B/C

Post by flash2705 » February 9th, 2015, 6:57 am

I don't speak nerd, so can you please explain what you're talking about?
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Re: Experimental Design B/C

Post by chinesesushi » February 9th, 2015, 7:24 am

flash2705 wrote:I don't speak nerd, so can you please explain what you're talking about?
You're in division B, I don't think you have to worry about it? Someone correct me if I'm wrong XD.
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Re: Experimental Design B/C

Post by bernard » February 9th, 2015, 7:58 am

chinesesushi wrote:
flash2705 wrote:I don't speak nerd, so can you please explain what you're talking about?
You're in division B, I don't think you have to worry about it? Someone correct me if I'm wrong XD.
If flash2705 is asking about standard deviation, the rule 4.j. allows both Div. B and C to choose from "mode or range or standard deviation or other relevant statistics."
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