R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
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> x <- c(98.85,98.86,98.86,98.89,98.85,98.85,98.85,98.96,98.99,99.21,99.29,99.32,99.32,99.17,99.13,99.12,99.23,99.25,99.25,99.36,99.43,99.57,99.64,99.68,99.68,99.52,99.69,99.7,99.85,99.94,99.94,99.93,100.19,100.57,100.76,100.86,100.86,100.39,100.61,100.67,100.81,100.86,100.86,100.98,101.03,101.37,101.64,101.68,101.68,101.25,101.24,101.11,101.08,101.09,101.09,101.62,101.66,101.96,102.04,102.02,102.02,101.51,101.62,101.83,102.06,102.14,102.14,102.59,102.92,103.31,103.54,103.58,103.58,102.83,102.86,103.03,103.2,103.28,103.28,103.79,103.92,104.26,104.41,104.45,99.92,99.18,99.18,99.35,99.62,99.67,99.72,100.08,100.39,100.77,101.03,101.07,101.29,101.1,101.2,101.15,101.24,101.16,100.81,101.02,101.15,101.06,101.17,101.22)
> 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,] 98.85 99.32  99.68 100.86 101.68 102.02 103.58  99.92 101.29
 [2,] 98.86 99.17  99.52 100.39 101.25 101.51 102.83  99.18 101.10
 [3,] 98.86 99.13  99.69 100.61 101.24 101.62 102.86  99.18 101.20
 [4,] 98.89 99.12  99.70 100.67 101.11 101.83 103.03  99.35 101.15
 [5,] 98.85 99.23  99.85 100.81 101.08 102.06 103.20  99.62 101.24
 [6,] 98.85 99.25  99.94 100.86 101.09 102.14 103.28  99.67 101.16
 [7,] 98.85 99.25  99.94 100.86 101.09 102.14 103.28  99.72 100.81
 [8,] 98.96 99.36  99.93 100.98 101.62 102.59 103.79 100.08 101.02
 [9,] 98.99 99.43 100.19 101.03 101.66 102.92 103.92 100.39 101.15
[10,] 99.21 99.57 100.57 101.37 101.96 103.31 104.26 100.77 101.06
[11,] 99.29 99.64 100.76 101.64 102.04 103.54 104.41 101.03 101.17
[12,] 99.32 99.68 100.86 101.68 102.02 103.58 104.45 101.07 101.22
> 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]  98.98167  99.34583 100.05250 100.98000 101.48667 102.43833 103.57417
[8]  99.99833 101.13083
> arr.sd
[1] 0.1832948 0.1946306 0.4470738 0.3969658 0.3859659 0.7342013 0.5858399
[8] 0.6784050 0.1258757
> arr.range
[1] 0.47 0.56 1.34 1.29 0.96 2.07 1.62 1.89 0.48
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -7.54816      0.07893  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -99.49          21.34  

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

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

Coefficients:
(Intercept)     arr.mean  
   -20.7451       0.2174  

> postscript(file="/var/wessaorg/rcomp/tmp/15ggw1452545030.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/2ewsp1452545030.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/3qezj1452545030.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4grfk1452545030.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5cqh01452545030.tab") 
> 
> try(system("convert tmp/15ggw1452545030.ps tmp/15ggw1452545030.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ewsp1452545030.ps tmp/2ewsp1452545030.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.825   0.155   0.990