R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(88.52,90.15,88.63,88.32,88.51,88.53,88.35,88.4,88.41,88.47,88.46,89.28,89.11,90.74,89.49,88.62,89.09,89.14,89.45,89.33,89.44,89.54,89.52,90.48,90.04,91.93,91.25,89.27,90.57,90.79,90.83,90.76,91.29,91.48,91.63,92.63,91.7,93.86,92.45,92.03,92.71,93.15,92.98,92.73,93.29,93.2,93.34,93.95,93.43,95.67,94.02,93.51,94.6,94.27,94.05,94.1,94.51,94.53,94.2,93.58,94.94,96.24,95.77,94.41,95.09,95.37,95.17,95.05,95.33,95.42,95.95,96.12,96.94,98.73,98.03,97.42,98.39,98.77,98.46,98.3,98.25,98.33,98.61,98.99,98.8,100.26,100.85,98.87,99.81,100.44,100.07,99.8,99.77,99.9,100.58,100.86,101.05,101.3,101.45,101.13,101.38,101.03,100.79,100.84,101.17,101.36,101.14,101.24)
> 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,] 88.52 89.11 90.04 91.70 93.43 94.94 96.94  98.80 101.05
 [2,] 90.15 90.74 91.93 93.86 95.67 96.24 98.73 100.26 101.30
 [3,] 88.63 89.49 91.25 92.45 94.02 95.77 98.03 100.85 101.45
 [4,] 88.32 88.62 89.27 92.03 93.51 94.41 97.42  98.87 101.13
 [5,] 88.51 89.09 90.57 92.71 94.60 95.09 98.39  99.81 101.38
 [6,] 88.53 89.14 90.79 93.15 94.27 95.37 98.77 100.44 101.03
 [7,] 88.35 89.45 90.83 92.98 94.05 95.17 98.46 100.07 100.79
 [8,] 88.40 89.33 90.76 92.73 94.10 95.05 98.30  99.80 100.84
 [9,] 88.41 89.44 91.29 93.29 94.51 95.33 98.25  99.77 101.17
[10,] 88.47 89.54 91.48 93.20 94.53 95.42 98.33  99.90 101.36
[11,] 88.46 89.52 91.63 93.34 94.20 95.95 98.61 100.58 101.14
[12,] 89.28 90.48 92.63 93.95 93.58 96.12 98.99 100.86 101.24
> 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]  88.66917  89.49583  91.03917  92.94917  94.20583  95.40500  98.26833
[8] 100.00083 101.15667
> arr.sd
[1] 0.5292612 0.5845816 0.8794260 0.6717746 0.6066819 0.5336410 0.5799660
[8] 0.6688179 0.2062802
> arr.range
[1] 1.83 2.12 3.36 2.25 2.24 1.83 2.05 2.06 0.66
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    2.30023     -0.01814  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       18.428         -4.182  

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

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

Coefficients:
(Intercept)     arr.mean  
    9.79422     -0.08194  

> postscript(file="/var/wessaorg/rcomp/tmp/1ncx31447949811.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/2bajz1447949811.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/3yfx71447949811.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/47j671447949811.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5yrh11447949811.tab") 
> 
> try(system("convert tmp/1ncx31447949811.ps tmp/1ncx31447949811.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bajz1447949811.ps tmp/2bajz1447949811.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.882   0.142   1.022