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...differences from the mean fusion distance (i.e. The Best Cut Test). To perform a cluster analysis I'm using: x <- dist(mydata, method = "euclidean") # distance matrix y <- hclust(x, method="ward") #clustering (i.e. fusion) method plot(y) # display dendogram Thanks, kbrownk

...at I will measure separately, so my csv file actually looks like this: Bin: 1,2,3, ... ,10 #Observations: 23,42,1,... 56 Bin: 1,2,3, ... ,10 #Observations: 13,33,32,...98 . . . Bin: 1,2,3, ... ,10 #Observations: 11,76,55,...46 I want to automate the process. Thanks for any advice, kbrownk

...efine 3 clusters. Will cutree look back at the cluster tree created by the Ward's method and then take the 3 largest distance values from among these 62 potential groups so that when I use Dunn index, those will be the only distances considered? I can post code and/or data if helpful. Thanks, kbrownk

...nificant for Hartigan's dip test? dip(x = rnorm(1000)) I get dip scores of around 0.0008 which based on p values taken from the table (at N=1000), using the command: qDiptab, are 0.02 < p < 0.05. Anyone familiar with Hartigan's dip test and what I may not be understanding? Thanks, kbrownk

...n use ks.test first. I used to use SPSS but am really trying to jump into R instead, but I find the help to assume too heavy of statistical knowledge. I'm guessing I have a long road before I get this, so any bits of information that may help me get a bit further will be appreciated! Thanks, kbrownk

I have 3 columns of data and want to plot each row as a point in a scatter plot and want one column to be represented as a color gradient (e.g. larger values being more red). Anyone know the command or package for this? Thanks, KB