Greetings,
I conducted an indoor plant rooting test involving 9 treatments (including 1 control). These tests were repeated by using 2 clones (siblings) and replicated across 2 flats with the plant trays (3" x 3") in random locations. Each flat contained 18 test trays with the 2 sibling clones each having 9 treatments. Each tray contained 3 cuttings.
I scored the rooting results for each tray into 3 categories:
[LIST=1]
[*]The total number of all roots that are longer than 1 mm (abv. "Roots>1mm").
[*]The percent of cuttings with root lengths longer than 20 mm (abv. "%Roots>20mm).
[*]The percent of cuttings that have any roots > 1 mm (abv. "%Rooted).
[/list]
Both flats contain the same tests so in theory, both should have similar results for each clone/treatment. I need to apply a statistical test that will compare the Flat 1 and Flat 2 values for the SAME clones and provide a P value that the 2 results might be the same. I was thinking the
Fisher Exact|http://en.wikipedia.org/wiki/Fisher%27s_exact_test test would work, but I am not sure...
Below is the data for the 1 control clone:
| Treatment Name | Flat1 | Flat2 |
| %Roots>20mm | 0.66 | 0.66 |
| %Rooted | 1 | 1 |
| Roots>1mm | 31 | 19 |
Note that the only difference is that the Flat2 samples had 12 less roots than the Flat1 samples. What statistical test would be appropriate to compare these 2 sets of results? Please show and explain your results with the P value.
Thanks in advance!
Pat
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