R version 3.2.2 (2015-08-14) -- "Fire Safety"
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> x <- c(91.99,92.17,92.19,92.24,92.19,92.21,92.22,92.14,92.43,92.93,93.01,93.07,93.08,93.11,93.21,93.49,93.48,93.51,93.52,93.49,93.76,94.25,94.42,94.45,94.45,94.53,94.78,95.05,95.21,95.23,95.23,95.34,95.93,96.75,97.15,97.21,97.21,97.35,97.44,97.34,97.44,97.43,97.43,97.47,97.69,98.54,98.64,98.72,98.72,98.73,98.68,98.75,98.73,98.74,98.75,98.85,99.14,99.83,99.93,100,100,100.08,100.25,100.4,100.33,100.29,100.29,100.32,100.82,101.42,101.46,101.55,101.56,101.56,101.6,101.66,101.82,101.94,101.95,101.93,102.26,102.65,102.9,102.94,99.14,99.18,99.23,99.32,99.46,99.5,99.95,100.13,100.43,101.09,101.27,101.29,101.04,101.14,101.11,101.01,101.08,101.06,101.26,101.32,101.4,101.85,102.12,102.15)
> 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,] 91.99 93.08 94.45 97.21  98.72 100.00 101.56  99.14 101.04
 [2,] 92.17 93.11 94.53 97.35  98.73 100.08 101.56  99.18 101.14
 [3,] 92.19 93.21 94.78 97.44  98.68 100.25 101.60  99.23 101.11
 [4,] 92.24 93.49 95.05 97.34  98.75 100.40 101.66  99.32 101.01
 [5,] 92.19 93.48 95.21 97.44  98.73 100.33 101.82  99.46 101.08
 [6,] 92.21 93.51 95.23 97.43  98.74 100.29 101.94  99.50 101.06
 [7,] 92.22 93.52 95.23 97.43  98.75 100.29 101.95  99.95 101.26
 [8,] 92.14 93.49 95.34 97.47  98.85 100.32 101.93 100.13 101.32
 [9,] 92.43 93.76 95.93 97.69  99.14 100.82 102.26 100.43 101.40
[10,] 92.93 94.25 96.75 98.54  99.83 101.42 102.65 101.09 101.85
[11,] 93.01 94.42 97.15 98.64  99.93 101.46 102.90 101.27 102.12
[12,] 93.07 94.45 97.21 98.72 100.00 101.55 102.94 101.29 102.15
> 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]  92.39917  93.64750  95.57167  97.72500  99.07083 100.60083 102.06417
[8]  99.99917 101.37833
> arr.sd
[1] 0.3782365 0.4797371 0.9701062 0.5598945 0.5269890 0.5640190 0.5081599
[8] 0.8354798 0.4215951
> arr.range
[1] 1.08 1.37 2.76 1.51 1.32 1.55 1.38 2.15 1.14
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   0.369724     0.002172  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -5.256          1.019  

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

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

Coefficients:
(Intercept)     arr.mean  
   2.247619    -0.006764  

> postscript(file="/var/wessaorg/rcomp/tmp/1154h1447876996.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/2yuzo1447876996.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/3q7sh1447876996.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4pg0c1447876996.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/58fsf1447876996.tab") 
> 
> try(system("convert tmp/1154h1447876996.ps tmp/1154h1447876996.png",intern=TRUE))
character(0)
> try(system("convert tmp/2yuzo1447876996.ps tmp/2yuzo1447876996.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.848   0.169   1.016