R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(84.71,85.17,84.93,85.1,85.19,85.38,85.95,86.04,85.68,85.79,85.79,86.05,86.14,86.82,86.93,87.03,87.13,87.09,87.65,87.6,87.03,87.12,87.08,87.56,87.31,87.89,88.2,87.7,88.19,88.65,89.48,89.65,89.34,89.73,89.77,90.26,90.03,91.09,90.94,91.03,91.14,91.51,91.99,91.91,91.8,91.8,91.44,91.83,91.46,92.17,91.91,92.06,92.33,92.73,93.35,93.28,93.22,93.31,93.21,93.14,93.82,94.18,94.44,94.35,94.38,94.72,95.25,95.16,94.9,95.09,95.22,95.39,96.57,97.05,97.11,97.08,97.5,97.92,98.44,98.44,98.06,98.2,98.19,98.36,98.41,98.97,99.45,98.95,99.7,100.12,100.62,100.75,100.47,100.71,100.85,101.03,101.13,101.38,101.73,101.89,102.02,102.11,102.77,102.49,102.52,102.69,102.32,102.6)
> 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,] 84.71 86.14 87.31 90.03 91.46 93.82 96.57  98.41 101.13
 [2,] 85.17 86.82 87.89 91.09 92.17 94.18 97.05  98.97 101.38
 [3,] 84.93 86.93 88.20 90.94 91.91 94.44 97.11  99.45 101.73
 [4,] 85.10 87.03 87.70 91.03 92.06 94.35 97.08  98.95 101.89
 [5,] 85.19 87.13 88.19 91.14 92.33 94.38 97.50  99.70 102.02
 [6,] 85.38 87.09 88.65 91.51 92.73 94.72 97.92 100.12 102.11
 [7,] 85.95 87.65 89.48 91.99 93.35 95.25 98.44 100.62 102.77
 [8,] 86.04 87.60 89.65 91.91 93.28 95.16 98.44 100.75 102.49
 [9,] 85.68 87.03 89.34 91.80 93.22 94.90 98.06 100.47 102.52
[10,] 85.79 87.12 89.73 91.80 93.31 95.09 98.20 100.71 102.69
[11,] 85.79 87.08 89.77 91.44 93.21 95.22 98.19 100.85 102.32
[12,] 86.05 87.56 90.26 91.83 93.14 95.39 98.36 101.03 102.60
> 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]  85.48167  87.09833  88.84750  91.37583  92.68083  94.74167  97.74333
[8] 100.00250 102.13750
> arr.sd
[1] 0.4594034 0.4050327 0.9723273 0.5647921 0.6633724 0.5017756 0.6500536
[8] 0.8818176 0.5268970
> arr.range
[1] 1.34 1.51 2.95 1.96 1.89 1.57 1.87 2.62 1.64
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  -0.068086     0.007426  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -6.922          1.414  

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

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

Coefficients:
(Intercept)     arr.mean  
    0.56402      0.01461  

> postscript(file="/var/wessaorg/rcomp/tmp/1elog1448190383.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/2kjut1448190383.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/3kaot1448190383.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4vhwu1448190383.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5odle1448190383.tab") 
> 
> try(system("convert tmp/1elog1448190383.ps tmp/1elog1448190383.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kjut1448190383.ps tmp/2kjut1448190383.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.828   0.145   0.978