R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(85.13,85.54,85.47,85.78,86.07,86.05,86.32,86.43,86.41,86.38,86.59,86.68,86.87,87.32,87.13,87.42,87.22,87.17,87.52,87.49,87.53,87.93,88.54,88.96,89.3,90.01,90.52,90.64,91.25,91.59,92.09,91.81,92.03,92.15,91.98,92.11,92.28,92.53,91.97,92.05,91.87,91.49,91.48,91.63,91.46,91.61,91.7,91.87,92.21,92.65,92.83,93.02,93.33,93.35,93.45,93.51,93.8,93.94,94.02,94.26,94.71,95.26,95.54,95.69,96.03,96.4,96.55,96.45,96.65,96.84,97.21,97.31,97.91,98.51,98.54,98.52,98.66,98.53,98.71,98.92,98.96,99.25,99.32,99.41,99.36,99.58,99.77,99.77,100.03,100.2,100.24,100.1,100.03,100.18,100.29,100.41,100.6,100.75,100.79,100.44,100.29,100.34,100.46,100.12,100.06,100.28,100.28,100.4)
> 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] 108
> (np <- floor(n / par1))
[1] 9
> 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]   [,9]
 [1,] 85.13 86.87 89.30 92.28 92.21 94.71 97.91  99.36 100.60
 [2,] 85.54 87.32 90.01 92.53 92.65 95.26 98.51  99.58 100.75
 [3,] 85.47 87.13 90.52 91.97 92.83 95.54 98.54  99.77 100.79
 [4,] 85.78 87.42 90.64 92.05 93.02 95.69 98.52  99.77 100.44
 [5,] 86.07 87.22 91.25 91.87 93.33 96.03 98.66 100.03 100.29
 [6,] 86.05 87.17 91.59 91.49 93.35 96.40 98.53 100.20 100.34
 [7,] 86.32 87.52 92.09 91.48 93.45 96.55 98.71 100.24 100.46
 [8,] 86.43 87.49 91.81 91.63 93.51 96.45 98.92 100.10 100.12
 [9,] 86.41 87.53 92.03 91.46 93.80 96.65 98.96 100.03 100.06
[10,] 86.38 87.93 92.15 91.61 93.94 96.84 99.25 100.18 100.28
[11,] 86.59 88.54 91.98 91.70 94.02 97.21 99.32 100.29 100.28
[12,] 86.68 88.96 92.11 91.87 94.26 97.31 99.41 100.41 100.40
> 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]  86.07083  87.59167  91.29000  91.82833  93.36417  96.22000  98.77000
[8]  99.99667 100.40083
> arr.sd
[1] 0.4913147 0.6074213 0.9559194 0.3362854 0.6052867 0.7927398 0.4260815
[8] 0.3141607 0.2252860
> arr.range
[1] 1.55 2.09 2.85 1.07 2.05 2.60 1.50 1.05 0.73
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    2.28351     -0.01868  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       17.608         -4.038  

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

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

Coefficients:
(Intercept)     arr.mean  
    6.96437     -0.05581  

> postscript(file="/var/wessaorg/rcomp/tmp/1jhd21447939475.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/2w3g41447939475.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/307b61447939475.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4fwbx1447939475.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5x13o1447939475.tab") 
> 
> try(system("convert tmp/1jhd21447939475.ps tmp/1jhd21447939475.png",intern=TRUE))
character(0)
> try(system("convert tmp/2w3g41447939475.ps tmp/2w3g41447939475.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.982   0.156   1.138