Experimental Design B/C

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Re: Experimental Design B/C

Postby Anomaly » October 14th, 2018, 12:02 pm

dxu46 wrote:
Anomaly wrote:What does the rubric mean in the quantitative data section where it says "Report most relevant data"?

Making a presentation on expd for middle schoolers and I come across that and have no idea what it means.

That's the condensed data table with important data such as averages.

ah alright that makes sense thanks
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Re: Experimental Design B/C

Postby Jacobi » October 15th, 2018, 8:15 am

Anomaly wrote:What does the rubric mean in the quantitative data section where it says "Report most relevant data"?

Making a presentation on expd for middle schoolers and I come across that and have no idea what it means.


I think it means that you should report data that is relevant to the hypothesis.

For example, if you're doing an XP with ball drop height v. drop time, you wouldn't report bounce height.

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Re: Experimental Design B/C

Postby pal_420 » October 24th, 2018, 9:00 pm

What do the rules mean by age-appropriate statistic? Does this mean we can't have more complex stuff like ANOVA?

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Re: Experimental Design B/C

Postby Jacobi » October 25th, 2018, 6:59 am

pal_420 wrote:What do the rules mean by age-appropriate statistic? Does this mean we can't have more complex stuff like ANOVA?

I think it means that you shouldn't be doing mode or range for Division C.
Who knows? You might want Pearson Correlation.

Also, how would ANOVA even apply to XPD data?

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Re: Experimental Design B/C

Postby nicholasmaurer » October 25th, 2018, 7:48 am

Jacobi wrote:
pal_420 wrote:What do the rules mean by age-appropriate statistic? Does this mean we can't have more complex stuff like ANOVA?

I think it means that you shouldn't be doing mode or range for Division C.
Who knows? You might want Pearson Correlation.

Also, how would ANOVA even apply to XPD data?


Many proctors will be unfamiliar with ANOVA, so I would not recommend using it for your statistical analysis. It is certainly not necessary to do so.

At the Division C level, I would generally recommend you choose either Pearson's correlation coefficient (r and r^2) or Student's t-test. These will cover almost every scenario and are easy to calculate using a graphing calculator. It is important that you understand and interpret the meaning of the results, rather than simply reporting them.

Mean and standard deviation will almost always be the best measures of center and spread to report. Occasionally, median might be preferred, but you're unlikely to have a sufficient sample size to know if your data is skewed.
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Re: Experimental Design B/C

Postby dxu46 » October 29th, 2018, 4:05 pm

nicholasmaurer wrote:
Jacobi wrote:
pal_420 wrote:What do the rules mean by age-appropriate statistic? Does this mean we can't have more complex stuff like ANOVA?

I think it means that you shouldn't be doing mode or range for Division C.
Who knows? You might want Pearson Correlation.

Also, how would ANOVA even apply to XPD data?


Many proctors will be unfamiliar with ANOVA, so I would not recommend using it for your statistical analysis. It is certainly not necessary to do so.

At the Division C level, I would generally recommend you choose either Pearson's correlation coefficient (r and r^2) or Student's t-test. These will cover almost every scenario and are easy to calculate using a graphing calculator. It is important that you understand and interpret the meaning of the results, rather than simply reporting them.

Mean and standard deviation will almost always be the best measures of center and spread to report. Occasionally, median might be preferred, but you're unlikely to have a sufficient sample size to know if your data is skewed.

What about for division B? A lot of the statistics would be much more simpler with an algorithm on a graphing calculator, but that's taken away.
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Re: Experimental Design B/C

Postby UTF-8 U+6211 U+662F » October 29th, 2018, 4:09 pm

dxu46 wrote:
nicholasmaurer wrote:
Jacobi wrote:I think it means that you shouldn't be doing mode or range for Division C.
Who knows? You might want Pearson Correlation.

Also, how would ANOVA even apply to XPD data?


Many proctors will be unfamiliar with ANOVA, so I would not recommend using it for your statistical analysis. It is certainly not necessary to do so.

At the Division C level, I would generally recommend you choose either Pearson's correlation coefficient (r and r^2) or Student's t-test. These will cover almost every scenario and are easy to calculate using a graphing calculator. It is important that you understand and interpret the meaning of the results, rather than simply reporting them.

Mean and standard deviation will almost always be the best measures of center and spread to report. Occasionally, median might be preferred, but you're unlikely to have a sufficient sample size to know if your data is skewed.

What about for division B? A lot of the statistics would be much more simpler with an algorithm on a graphing calculator, but that's taken away.

I would say mean and standard deviation are fairly easy to calculate by hand, but you could also use the mean absolute deviation which takes the absolute values instead of squaring and then square rooting (even easier by hand!).

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Re: Experimental Design B/C

Postby Jacobi » October 29th, 2018, 4:10 pm

dxu46 wrote:
nicholasmaurer wrote:
Jacobi wrote:I think it means that you shouldn't be doing mode or range for Division C.
Who knows? You might want Pearson Correlation.

Also, how would ANOVA even apply to XPD data?


Many proctors will be unfamiliar with ANOVA, so I would not recommend using it for your statistical analysis. It is certainly not necessary to do so.

At the Division C level, I would generally recommend you choose either Pearson's correlation coefficient (r and r^2) or Student's t-test. These will cover almost every scenario and are easy to calculate using a graphing calculator. It is important that you understand and interpret the meaning of the results, rather than simply reporting them.

Mean and standard deviation will almost always be the best measures of center and spread to report. Occasionally, median might be preferred, but you're unlikely to have a sufficient sample size to know if your data is skewed.

What about for division B? A lot of the statistics would be much more simpler with an algorithm on a graphing calculator, but that's taken away.

Given that they say "age-appropriate", they would expect mean, median, range, mode???? :lol:, maybe Standard Deviation. Those formulae are easy to memorize and execute on a 4-function or non-programmable scientific calculator.

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Re: Experimental Design B/C

Postby dxu46 » October 29th, 2018, 4:12 pm

UTF-8 U+6211 U+662F wrote:
dxu46 wrote:
nicholasmaurer wrote:
Many proctors will be unfamiliar with ANOVA, so I would not recommend using it for your statistical analysis. It is certainly not necessary to do so.

At the Division C level, I would generally recommend you choose either Pearson's correlation coefficient (r and r^2) or Student's t-test. These will cover almost every scenario and are easy to calculate using a graphing calculator. It is important that you understand and interpret the meaning of the results, rather than simply reporting them.

Mean and standard deviation will almost always be the best measures of center and spread to report. Occasionally, median might be preferred, but you're unlikely to have a sufficient sample size to know if your data is skewed.

What about for division B? A lot of the statistics would be much more simpler with an algorithm on a graphing calculator, but that's taken away.

I would say mean and standard deviation are fairly easy to calculate by hand, but you could also use the mean absolute deviation which takes the absolute values instead of squaring and then square rooting (even easier by hand!).

Alright, thanks.

Just wondering, are there any ES's out there on the forums? I'm curious on how certain sections are judged (i.e. Analysis, Qualitative, Statistics)
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Re: Experimental Design B/C

Postby UTF-8 U+6211 U+662F » October 29th, 2018, 4:14 pm

dxu46 wrote:
UTF-8 U+6211 U+662F wrote:
dxu46 wrote:What about for division B? A lot of the statistics would be much more simpler with an algorithm on a graphing calculator, but that's taken away.

I would say mean and standard deviation are fairly easy to calculate by hand, but you could also use the mean absolute deviation which takes the absolute values instead of squaring and then square rooting (even easier by hand!).

Alright, thanks.

(Also see Jacobi's post, although I'm skeptical of range being a good indicator of anything, and you probably won't have a mode)

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Re: Experimental Design B/C

Postby dxu46 » October 29th, 2018, 4:16 pm

UTF-8 U+6211 U+662F wrote:
dxu46 wrote:
UTF-8 U+6211 U+662F wrote:I would say mean and standard deviation are fairly easy to calculate by hand, but you could also use the mean absolute deviation which takes the absolute values instead of squaring and then square rooting (even easier by hand!).

Alright, thanks.

(Also see Jacobi's post, although I'm skeptical of range being a good indicator of anything, and you probably won't have a mode)

Right, unless it's a very broad measurement or rounded, modes are not a thing.
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Re: Experimental Design B/C

Postby Galahad » November 1st, 2018, 7:49 pm

Hey, does anyone know what:
(M) suggestions for other ways to look at hypothesis means?
(K) important info about data collection?
(J) all data discussed and interpreted?
means?

We never were really given clarification for it and even our coach doesn't know.
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Re: Experimental Design B/C

Postby dxu46 » November 1st, 2018, 8:10 pm

Galahad wrote:Hey, does anyone know what:
(M) suggestions for other ways to look at hypothesis means?
(K) important info about data collection?
(J) all data discussed and interpreted?
means?

We never were really given clarification for it and even our coach doesn't know.

M: Just other interpretations - i.e. different IV levels. The 3 parts are different experiment same topic, different IV, and improve the current one.
K: Maybe give a short explanation of how the data was collected and the role of the error in it.
J: In an experiment, all the parts need to be discussed, or else that part was of no use. Analysis is a means to draw conclusions from all parts of the experiment.

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Re: Experimental Design B/C

Postby UTF-8 U+6211 U+662F » November 2nd, 2018, 4:54 pm

Wait, is it new that Experimental Design is in the at-the-beginning-of-the-competition time block (same block as Disease Detectives)? Do we know how definite this is?

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Re: Experimental Design B/C

Postby kate! » November 2nd, 2018, 5:38 pm

UTF-8 U+6211 U+662F wrote:Wait, is it new that Experimental Design is in the at-the-beginning-of-the-competition time block (same block as Disease Detectives)? Do we know how definite this is?

New York states had this last year, so maybe it was in other states as well, but not nationals afaik. It's a good system, honestly, because now no one has any advantages or disadvantages.
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