R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(80.44,80.9,81.03,81.6,81.56,82.08,83.44,83.55,82.63,82.43,82.42,82.48,82.51,83.23,83.41,83.88,83.96,84.32,85.82,85.72,84.36,84.36,84.36,85.08,84.95,85.62,86.22,86.4,86.71,87.51,89.22,89.43,88.24,88.9,88.78,89.25,88.8,89.46,89.66,90.29,90.08,90.42,92.14,92.09,91.35,91.22,90.99,91.48,90.98,91.52,91.62,92.12,92.26,92.18,94.12,93.82,93.2,93.34,93.11,93.63,93.29,93.69,94.19,94.82,94.52,94.94,96.87,96.6,95.43,95.56,95.37,96,95.6,96.17,96.26,97.2,97.23,97.74,99.37,99.37,98.22,98.27,97.98,98.53,97.98,98.63,98.74,99.37,99.51,99.66,101.62,101.71,100.49,100.81,100.48,101.01,100.62,101.12,101.45,101.34,101.39,101.93,102.42,102.18,102.72,102.43,102.35,102.69)
> 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,] 80.44 82.51 84.95 88.80 90.98 93.29 95.60  97.98 100.62
 [2,] 80.90 83.23 85.62 89.46 91.52 93.69 96.17  98.63 101.12
 [3,] 81.03 83.41 86.22 89.66 91.62 94.19 96.26  98.74 101.45
 [4,] 81.60 83.88 86.40 90.29 92.12 94.82 97.20  99.37 101.34
 [5,] 81.56 83.96 86.71 90.08 92.26 94.52 97.23  99.51 101.39
 [6,] 82.08 84.32 87.51 90.42 92.18 94.94 97.74  99.66 101.93
 [7,] 83.44 85.82 89.22 92.14 94.12 96.87 99.37 101.62 102.42
 [8,] 83.55 85.72 89.43 92.09 93.82 96.60 99.37 101.71 102.18
 [9,] 82.63 84.36 88.24 91.35 93.20 95.43 98.22 100.49 102.72
[10,] 82.43 84.36 88.90 91.22 93.34 95.56 98.27 100.81 102.43
[11,] 82.42 84.36 88.78 90.99 93.11 95.37 97.98 100.48 102.35
[12,] 82.48 85.08 89.25 91.48 93.63 96.00 98.53 101.01 102.69
> 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]  82.04667  84.25083  87.60250  90.66500  92.65833  95.10667  97.66167
[8] 100.00083 101.88667
> arr.sd
[1] 0.9715530 0.9700277 1.5746637 1.0547081 1.0117566 1.0920567 1.2142999
[8] 1.2057699 0.6842691
> arr.range
[1] 3.11 3.31 4.48 3.34 3.14 3.58 3.77 3.73 2.10
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   1.663847    -0.006246  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       2.7189        -0.5875  

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

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

Coefficients:
(Intercept)     arr.mean  
      5.522       -0.023  

> postscript(file="/var/wessaorg/rcomp/tmp/1hhvr1447956991.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/2jsf51447956991.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/36jfi1447956991.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4wn6x1447956991.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5wj281447956991.tab") 
> 
> try(system("convert tmp/1hhvr1447956991.ps tmp/1hhvr1447956991.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jsf51447956991.ps tmp/2jsf51447956991.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.866   0.162   1.029