[R] understanding patterns in categorical vs. continuous data

Berton Gunter gunter.berton at gene.com
Thu Jan 26 20:25:02 CET 2006

UC Davis has a statistical department, I would suggest you get consulting
help from them. Do they have a consulting service?

-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA
"The business of the statistician is to catalyze the scientific learning
process."  - George E. P. Box

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Dylan Beaudette
> Sent: Thursday, January 26, 2006 11:11 AM
> To: r-help at stat.math.ethz.ch
> Subject: [R] understanding patterns in categorical vs. continuous data
> Greetings,
> I have a set of bivariate data: one variable (vegetation 
> type) which is 
> categorical, and one (computed annual insolation) which is 
> continuous. 
> Plotting veg_type ~ insolation produces a nice overview of 
> the patterns that 
> I can see in the source data. However, due to the large 
> number of samples 
> (1,000), and the apparent "spread" in the distribution of a 
> single vegetation 
> type over a range of insolation values- I having a hard time 
> quantitatively 
> describing the relationship between the two variables. 
> Here is a link to a sample graph:
> http://casoilresource.lawr.ucdavis.edu/drupal/node/162
> Since the data along each vegetation type "line" is not a 
> distribution in the 
> traditional sense, I am having problems applying descriptive 
> statistical 
> methods. Conceptually, I would like to some how describe the 
> variation with 
> insolation, along each vegetation type "line".
> Any guidance, or suggested reading material would be greatly 
> appreciated.
> -- 
> Dylan Beaudette
> Soils and Biogeochemistry Graduate Group
> University of California at Davis
> 530.754.7341
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide! 
> http://www.R-project.org/posting-guide.html

More information about the R-help mailing list