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> x <- c(85.95,86.41,86.42,86.81,86.71,86.7,87.07,86.96,87.04,87.5,88.32,88.56,88.92,89.56,90.21,90.42,91.23,91.73,92.21,91.65,91.8,91.63,91.09,90.89,90.98,91.29,90.77,90.96,90.89,90.72,90.66,90.94,90.7,90.74,90.98,91.13,91.54,91.93,92.27,92.59,92.96,92.95,92.99,93.05,93.34,93.47,93.59,93.96,94.49,95.04,95.52,95.75,96.07,96.37,96.48,96.4,96.66,96.81,97.19,97.23,97.94,98.52,98.73,98.8,98.77,98.54,98.72,99.15,99.32,99.5,99.39,99.4,99.37,99.69,99.83,99.79,99.94,100.11,100.21,100.15,100.21,100.13,100.2,100.36,100.5,100.66,100.72,100.41,100.3,100.38,100.55,100.17,100.09,100.22,100.09,99.98)
> par1 = '12'
> par1 <- '12'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P. (2012), Standard Deviation-Mean Plot (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_smp.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 96
> (np <- floor(n / par1))
[1] 8
> arr <- array(NA,dim=c(par1,np))
> j <- 0
> k <- 1
> for (i in 1:(np*par1))
+ {
+ j = j + 1
+ arr[j,k] <- x[i]
+ if (j == par1) {
+ j = 0
+ k=k+1
+ }
+ }
> arr
       [,1]  [,2]  [,3]  [,4]  [,5]  [,6]   [,7]   [,8]
 [1,] 85.95 88.92 90.98 91.54 94.49 97.94  99.37 100.50
 [2,] 86.41 89.56 91.29 91.93 95.04 98.52  99.69 100.66
 [3,] 86.42 90.21 90.77 92.27 95.52 98.73  99.83 100.72
 [4,] 86.81 90.42 90.96 92.59 95.75 98.80  99.79 100.41
 [5,] 86.71 91.23 90.89 92.96 96.07 98.77  99.94 100.30
 [6,] 86.70 91.73 90.72 92.95 96.37 98.54 100.11 100.38
 [7,] 87.07 92.21 90.66 92.99 96.48 98.72 100.21 100.55
 [8,] 86.96 91.65 90.94 93.05 96.40 99.15 100.15 100.17
 [9,] 87.04 91.80 90.70 93.34 96.66 99.32 100.21 100.09
[10,] 87.50 91.63 90.74 93.47 96.81 99.50 100.13 100.22
[11,] 88.32 91.09 90.98 93.59 97.19 99.39 100.20 100.09
[12,] 88.56 90.89 91.13 93.96 97.23 99.40 100.36  99.98
> arr.mean <- array(NA,dim=np)
> arr.sd <- array(NA,dim=np)
> arr.range <- array(NA,dim=np)
> for (j in 1:np)
+ {
+ arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
+ arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
+ arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
+ }
> arr.mean
[1]  87.03750  90.94500  90.89667  92.88667  96.16750  98.89833  99.99917
[8] 100.33917
> arr.sd
[1] 0.7636292 0.9933277 0.1896088 0.7029979 0.8372479 0.4644417 0.2826645
[8] 0.2378868
> arr.range
[1] 2.61 3.29 0.63 2.42 2.74 1.56 0.99 0.74
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    3.51666     -0.03125  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
       23.011         -5.222  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    12.0724      -0.1078  

> postscript(file="/var/wessaorg/rcomp/tmp/1osg41448194411.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2ngzb1448194411.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/3vmn31448194411.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4ebs41448194411.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5b7u81448194411.tab") 
> 
> try(system("convert tmp/1osg41448194411.ps tmp/1osg41448194411.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ngzb1448194411.ps tmp/2ngzb1448194411.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.839   0.136   0.978