Hi all

I'm currently close to finishing my dissertation. I'm studying vegetational changes in quadrats (sample areas) inside and outside exclosures, to test for amounts of browsing damage from deer. I gathered my data over the winter (three study periods, November, December & January), so I want to know how much of the change in vegetation is from winter dieback.

To do this, I'm comparing change of height 'inside' November v December v January, 'outside' November v December v January and 'all quadrats' November v December v January with one-way ANOVAs. If 'inside' and 'all quadrats' have lower p-numbers, I am assuming that change was more significant in un-grazed areas and that therefore winter dieback is likely to have been an important factor in vegetation loss.

Here's an example:

In - p = 0.374

Out - p = 0.773

All - p = 0.456

Therefore, 'In' showed the most change, as there is a 37% chance that the null hypothesis that there is no significant difference between the means is true, the lowest chance of the three?

Is it possible to compare p-values in this way? I'm comparing a fixed number of sample points for each site. If not, can anyone recommend what test I should use in order to find out where change was greater?

Thanks in advance!

I'm currently close to finishing my dissertation. I'm studying vegetational changes in quadrats (sample areas) inside and outside exclosures, to test for amounts of browsing damage from deer. I gathered my data over the winter (three study periods, November, December & January), so I want to know how much of the change in vegetation is from winter dieback.

To do this, I'm comparing change of height 'inside' November v December v January, 'outside' November v December v January and 'all quadrats' November v December v January with one-way ANOVAs. If 'inside' and 'all quadrats' have lower p-numbers, I am assuming that change was more significant in un-grazed areas and that therefore winter dieback is likely to have been an important factor in vegetation loss.

Here's an example:

In - p = 0.374

Out - p = 0.773

All - p = 0.456

Therefore, 'In' showed the most change, as there is a 37% chance that the null hypothesis that there is no significant difference between the means is true, the lowest chance of the three?

Is it possible to compare p-values in this way? I'm comparing a fixed number of sample points for each site. If not, can anyone recommend what test I should use in order to find out where change was greater?

Thanks in advance!

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