R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(88.83,89.01,88.21,87.78,87.93,88.11,88.2,88.12,88.38,87.65,88.24,87.83,87.75,87.88,87.61,88.05,87.77,87.79,88.34,88.48,88.75,87.95,89.09,88.73,89.24,89.77,89.84,90.97,91.53,92.2,92.27,92.42,92.07,91.73,92.1,91.68,92.63,93.02,92.66,93.23,93.79,93.92,94.04,94.23,94.37,94.29,94.38,94,94.11,93.98,93.42,93.3,93.32,93.75,93.82,94.06,94.09,93.64,93.9,93.18,93.54,93.55,93.8,93.39,93.27,93.58,93.47,93.75,93.3,92.65,92.96,92.84,93.29,93.57,93.54,94.38,93.98,94.48,94.63,95.45,95.59,94.76,95.66,95.03,96.45,97.15,97.5,98.54,99.54,100.33,100.28,101.81,101.91,101.92,102.68,101.9,102.14,102.3,102.06,102.4,102.99,102.99,102.83,103.01,102.6,102.18,102.6,101.44)
> 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,] 88.83 87.75 89.24 92.63 94.11 93.54 93.29  96.45 102.14
 [2,] 89.01 87.88 89.77 93.02 93.98 93.55 93.57  97.15 102.30
 [3,] 88.21 87.61 89.84 92.66 93.42 93.80 93.54  97.50 102.06
 [4,] 87.78 88.05 90.97 93.23 93.30 93.39 94.38  98.54 102.40
 [5,] 87.93 87.77 91.53 93.79 93.32 93.27 93.98  99.54 102.99
 [6,] 88.11 87.79 92.20 93.92 93.75 93.58 94.48 100.33 102.99
 [7,] 88.20 88.34 92.27 94.04 93.82 93.47 94.63 100.28 102.83
 [8,] 88.12 88.48 92.42 94.23 94.06 93.75 95.45 101.81 103.01
 [9,] 88.38 88.75 92.07 94.37 94.09 93.30 95.59 101.91 102.60
[10,] 87.65 87.95 91.73 94.29 93.64 92.65 94.76 101.92 102.18
[11,] 88.24 89.09 92.10 94.38 93.90 92.96 95.66 102.68 102.60
[12,] 87.83 88.73 91.68 94.00 93.18 92.84 95.03 101.90 101.44
> 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]  88.19083  88.18250  91.31833  93.71333  93.71417  93.34167  94.53000
[8] 100.00083 102.46167
> arr.sd
[1] 0.4033149 0.4824959 1.1054150 0.6543607 0.3356800 0.3590096 0.8161216
[8] 2.1512891 0.4720137
> arr.range
[1] 1.36 1.48 3.18 1.75 0.93 1.15 2.37 6.23 1.57
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -3.91907      0.04974  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -19.999          4.299  

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

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

Coefficients:
(Intercept)     arr.mean  
   -11.4020       0.1451  

> postscript(file="/var/wessaorg/rcomp/tmp/1saxw1448213526.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/2jso71448213526.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/3eftc1448213526.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4ks9d1448213526.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5m0sc1448213526.tab") 
> 
> try(system("convert tmp/1saxw1448213526.ps tmp/1saxw1448213526.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jso71448213526.ps tmp/2jso71448213526.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.905   0.165   1.070