Hi Tom,
Thank you for the friendly and informative answer. It does explain a lot of
things, actually. As with any good answer, it inevitably leads to other
questions. In the first place, I need the arithmetic mean. It's what we
base our calculations on...
My code is currently this:
Metall<-c("Cu","Cu","Cu","Cu","Cu","Cu","Cu","Cu","Cu","Cr","Cr","Cr","Cr","
Cr","Cr","Cr","Cr","Cr","As","As","As","As","As","As","As","As","As","Pb","P
b","Pb","Pb","Pb","Pb","Pb","Pb","Pb","Zn","Zn","Zn","Zn","Zn","Zn","Zn","Zn
","Zn")
Halt<-c(85,13,13,340,18,13,88,24,12,216,33,21,454,20,18,88,30,21,1254,22,4.2
,1081,35,6,1772,192,7.6,43,20,12,3107,21,12,30,24,19,1109,57,46,269,68,50,58
5,131,52)
beanplot(Halt~Metall, log = "y", yaxt = "n", ylab="Halt
(mg/kg)",cex.lab=1.2)
axis(2,c(1,10,100,1000,10000))
polygon(c(0.2966510,0.2966510,1.4832033,1.4832033,3.6160162,3.6160162,4.4921
444,4.4921444,5.6968371,5.6968371),c(2.763021e-01,10,10,80,80,40,40,250,250,
2.763021e-01),col="#66FF0090", border="#66FF0090")
text(5.58,10,"<KM", cex=1.2, font=2)
polygon(c(0.2966510,0.29665101,1.4832033,1.4832033),c(10,25,25,10),col="#FFF
F0090",border="#FFFF0090")
polygon(c(1.4832033,1.4832033,2.5027348,2.5027348,3.6160162,3.6160162,4.4921
444,4.4921444,5.6968371,5.6968371,4.4921444,4.4921444,3.6160162,3.6160162,1.
4832033),c(80,150,150,200,200,400,400,500,500,250,250,40,40,80,80),col="#FFF
F0090",border="#FFFF0090")
text(5.54,350,"<MKM", cex=1.2, font=2)
polygon(c(0.2966510,0.2966510,5.6968371,5.6968371,4.4921444,4.4921444,3.6160
162,3.6160162,2.5027348,2.5027348,1.4832033,1.4832033),c(25,30085.997183,300
85.997183,500,500,400,400,200,200,150,150,25),col="#FF000090",border="#FF000
090")
text(5.54,2500,">MKM", cex=1.2, font=2)
The polygons convey information on whether each sample is higher than the
soil guideline value. If I take away, the log scale, the vast difference in
values obscures the polygons... Ideally I'd like the average beanline to be
the arithmetic mean or to be gone altogether. Can't seem to make beanplot do
this...
Sincerely,
Michael Hopgood