how to plot a distribution of mean and standard deviation
R. Michael Weylandt <michael.weylandt <at> gmail.com> writes:
It seems like the relevant plot would depend on what you are trying to investigate, but usually a scatterplot would well work for bivariate data with no other assumptions needed. I usually find ecdf() plots rather hard to interpret without playing around with the data elsewhere first and I'm not sure they make an enormous amount of sense for bivariate data in your case since they reorder inputs. Michael
[snip]
On Sun, Oct 23, 2011 at 6:51 AM, gj <gawesh <at> gmail.com> wrote:
Hi, I have the following data about courses (504) in a university, two attributes about the proportion of resources used (#resources_used / #resources_available), namely the average and the standard deviation. Thus I have: [1] n=504 rows [2] 1 id column and 2 attributes Here's a sample of the data:
[snip]
You could make a "caterpillar plot" as follows:
X <- read.csv("coursetmp.dat")
library(ggplot2)
X <- transform(X,courseid=reorder(courseid,average))
ggplot(X,aes(x=courseid,y=average,
ymin=average-2*std,ymax=average+2*std))+geom_point()+
geom_linerange()+coord_flip()
(Here the x and y axes are flipped because it's easier to plot & read
the course ID labels that way)
Of course, the answer to "how should I visualize these data?" always
depends on what you want to find out ...