R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(78.25,77.24,76.68,76.29,76.1,75.77,75.6,75.57,75.89,76.04,76.89,77,79.09,80.84,81.82,82.12,81.01,82.22,81.97,82.42,82.77,82.46,83.35,84.27,87.34,91.03,93.52,94.24,94.92,95.49,96.55,98.07,102.87,104.12,103.49,103.31,103.92,103.69,103.41,102.83,103,103.42,102.57,102.72,102.22,102.32,102.48,101.56,101.02,101.41,100.74,99.76,99.76,99.17,99.11,99.69,99.4,99.79,99.72,98.74,98.26,97.31,96.73,96.18,95.92,96.13,95.64,94.52,94.31,96.05,96.17,95.14,95.37,96.5,96.79,96.23,96,95.21,94.77,96.84,99.06,100.36,100.09,100.03,100.49,101,102.11,101.59,100.81,100.86,99.57,100.21,99.68,98.38,97.93,97.37,99.08,99.15,99.44,99.48,99.62,98.95,99.42,99.84,99.27,99.16,99.04,99.62)
> 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,] 78.25 79.09  87.34 103.92 101.02 98.26  95.37 100.49 99.08
 [2,] 77.24 80.84  91.03 103.69 101.41 97.31  96.50 101.00 99.15
 [3,] 76.68 81.82  93.52 103.41 100.74 96.73  96.79 102.11 99.44
 [4,] 76.29 82.12  94.24 102.83  99.76 96.18  96.23 101.59 99.48
 [5,] 76.10 81.01  94.92 103.00  99.76 95.92  96.00 100.81 99.62
 [6,] 75.77 82.22  95.49 103.42  99.17 96.13  95.21 100.86 98.95
 [7,] 75.60 81.97  96.55 102.57  99.11 95.64  94.77  99.57 99.42
 [8,] 75.57 82.42  98.07 102.72  99.69 94.52  96.84 100.21 99.84
 [9,] 75.89 82.77 102.87 102.22  99.40 94.31  99.06  99.68 99.27
[10,] 76.04 82.46 104.12 102.32  99.79 96.05 100.36  98.38 99.16
[11,] 76.89 83.35 103.49 102.48  99.72 96.17 100.09  97.93 99.04
[12,] 77.00 84.27 103.31 101.56  98.74 95.14 100.03  97.37 99.62
> 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]  76.44333  82.02833  97.07917 102.84500  99.85917  96.03000  97.27083
[8] 100.00000  99.33917
> arr.sd
[1] 0.7978190 1.3085928 5.4242778 0.6799532 0.8034297 1.1015939 2.0478035
[8] 1.4701144 0.2740092
> arr.range
[1]  2.68  5.18 16.78  2.36  2.67  3.95  5.59  4.74  0.89
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    0.17794      0.01446  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      0.43809       -0.07112  

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

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

Coefficients:
(Intercept)     arr.mean  
    2.91360      0.02188  

> postscript(file="/var/wessaorg/rcomp/tmp/1w23z1448046043.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/2d4b61448046043.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/3xj3f1448046043.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/428em1448046043.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5022g1448046043.tab") 
> 
> try(system("convert tmp/1w23z1448046043.ps tmp/1w23z1448046043.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d4b61448046043.ps tmp/2d4b61448046043.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.812   0.145   0.968