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...rranted)? I have a histogram and I want to see if the data fit a Poisson distribution. How do I do this? It is preferable if it could be done without having to install any or many packages. I use R Version 1.12 (1622) on OS X Thank-you very much, Tom Isenbarger -- Tom Isenbarger PhD isen@plantpath.wisc.edu 608.265.0850 [[alternative HTML version deleted]]

...tion. However, the normal scores plot suggest otherwise. Using R version 1.9.1 Thanks in advance. Ken ________________________________________________________ Kenneth E. Frost Research Assistant University of Wisconsin - Madison Dept. of Plant Pathology 1630 Linden Dr. Madison, WI 53706 kef at plantpath.wisc.edu

...d the R home pages and the R-help archives with no hits. How can I cluster data in R using UPGMA? I am not subscribed to the list (can't keep up with all the traffic!), so I would appreciate it if you could email directly to me (or to the list and to me). Thanks, Tom Isenbarger -- isen at plantpath.wisc.edu thomas a isenbarger (608) 265-0850

...at I would predict and what I want the plot to show. If I instead use plot(cmdscale(as.dist(dissmini))) the plot is the same. something like this: s4 s1 s5 s2 s3 Thanks for your help, Tom Isenbarger -- isen@plantpath.wisc.edu thomas a isenbarger (608) 265-0850 [[alternative text/enriched version deleted]]

...res for similarities, not high scores for dissimilarities. The only thought I had was to use the reciprocal of the BLAST score as some perverse measure of distance. I am not subscribed to the list, so can I ask for responses directly to my email address? Thank-you, Tom Isenbarger -- isen at plantpath.wisc.edu thomas a isenbarger (608) 265-0850

I am relatively new to R and am looking for advice, ideas or both... I have a data set that consists of pathogen population sizes on individual plant units in an experimental field plot. However, in order to estimate the pathogen population sizes I had to destroy the plant unit and could not determine if that plant unit became diseased or to what extent it would have become diseased. I