Spearman's Rank or Mann Whitney U Test? (A2 Biology Coursework) Watch

9emmacl2345
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This is for my A2 Edexcel Bio coursework. I investigated the effect of light intensity on the thickness of nettle leaves. So for the statistical test, which one do I use.

I tested it in 2 different areas (sun and shade) but in both, the light intensity varied. I thought it was mann whitney u because of the different areas, but apparently I have to do 2 man whitney u tests (one for light intensity and one for thickness). But then a classmate of mine told me that it might be spearman's rank because the light intensities have 10 different numbers for both areas (20 in total).

Any ideas? I only have a couple days until its due.
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Asklepios
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(Original post by gemmac123455)
This is for my A2 Edexcel Bio coursework. I investigated the effect of light intensity on the thickness of nettle leaves. So for the statistical test, which one do I use.

I tested it in 2 different areas (sun and shade) but in both, the light intensity varied. I thought it was mann whitney u because of the different areas, but apparently I have to do 2 man whitney u tests (one for light intensity and one for thickness). But then a classmate of mine told me that it might be spearman's rank because the light intensities have 10 different numbers for both areas (20 in total).

Any ideas? I only have a couple days until its due.
Light intensity and leaf thickness are both continuous parameters so you to measure the correlation I.e. Spearman's rank. You can then test for significance using a Students t test. You could do this for each of the two areas, then maybe pool all the data into one?

The area shouldn't really matter, and as such is pretty much just you replicating the experiment
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9emmacl2345
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(Original post by Asklepios)
Light intensity and leaf thickness are both continuous parameters so you to measure the correlation I.e. Spearman's rank. You can then test for significance using a Students t test. You could do this for each of the two areas, then maybe pool all the data into one?

The area shouldn't really matter, and as such is pretty much just you replicating the experiment
Thank you so much! I really appreciate it.
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9emmacl2345
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(Original post by Asklepios)
Light intensity and leaf thickness are both continuous parameters so you to measure the correlation I.e. Spearman's rank. You can then test for significance using a Students t test. You could do this for each of the two areas, then maybe pool all the data into one?

The area shouldn't really matter, and as such is pretty much just you replicating the experiment
Just another quick question. Would I do 2 different spearmans ranks (one for sun and one for shade) or would I just do one spearmans rank (combine the data for sun and shade)?


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(Original post by gemmac123455)
Just another quick question. Would I do 2 different spearmans ranks (one for sun and one for shade) or would I just do one spearmans rank (combine the data for sun and shade)?


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I think it really depends. Ideally, the only difference between the two areas would be sun/shade but there COULD be other differences (e.g. Soil pH, wind etc) that affect leaf thickness. So what I would do - plot leaf thickness on the y-axis against light intensity on the x-axis, and have a different colour of dot for each area. If the pattern of dots seems to follow the same general trend for both areas then you can pool your data together. If it follows a different pattern then that won't really work (like comparing mars bars and snickers).

Either way do 2 spearmans ranks initially, then see if you can combine them.
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