There are probably many, many way to handle this, but you might want to try some form of cluster analysis. Hierarchical trees or k-means analysis are good ways to get a quick intuitive overview of patterns in matrix datasets like yours. We often use these methods to explore expression patterns of genes (rows) over a range of conditions (columns) in DNA microarray studies. You could use our free, open source package MeV (http://www.tm4.org/mev.html) for this. MeV can take as input a simple tab-delimited text file of rows and columns that you can generate in Excel.
Regards, Nirmal Bhagabati The Institute for Genomic Research, Rockville, MD 20850 www.tigr.org On 4/6/06, Griffith Gilbert <[EMAIL PROTECTED]> wrote: > I have 107 willow occurences (individual trees). Let's call these the > Sampling Units (SUs). I have 8 quantitative environmental/physical > variables (e.g. elevation, valley width, stream slope, etc.) measured > around each SU. Therefore, I have 107 rows and 8 columns in my dataset. > How can I find out if there exist any differences between SUs based upon > the variables measured? >
