R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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> x <- c(100.64,100.93,101.41,102.07,102.42,102.53,102.43,102.6,102.65,102.74,102.82,103.2,102.75,103.09,103.71,104.3,104.58,104.71,104.44,104.57,104.95,105.49,106.03,106.48,106.25,106.7,107.6,108.05,108.72,109.17,109.08,109.04,109.34,109.37,108.96,108.77,108.11,108.67,109.05,109.43,109.62,109.85,109.34,109.65,109.69,109.91,110.09,110.44,109.9,110.25,111.26,111.74,111.91,111.95,111.63,111.85,112.16,112.49,112.66,113.39,112.92,113.44,114.68,115.38,115.48,115.41,114.92,115.16,115.89,116.25,116.43,116.83,116.17,116.78,117.98,118.53,118.43,118.29,117.85,118.27,119,119.33,119.17,119.57,118.62,119.09,120.19,120.17,120.29,120.35,119.88,120.04,120.52,120.43,120.34,120.75)
> 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] 96
> (np <- floor(n / par1))
[1] 8
> 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]
 [1,] 100.64 102.75 106.25 108.11 109.90 112.92 116.17 118.62
 [2,] 100.93 103.09 106.70 108.67 110.25 113.44 116.78 119.09
 [3,] 101.41 103.71 107.60 109.05 111.26 114.68 117.98 120.19
 [4,] 102.07 104.30 108.05 109.43 111.74 115.38 118.53 120.17
 [5,] 102.42 104.58 108.72 109.62 111.91 115.48 118.43 120.29
 [6,] 102.53 104.71 109.17 109.85 111.95 115.41 118.29 120.35
 [7,] 102.43 104.44 109.08 109.34 111.63 114.92 117.85 119.88
 [8,] 102.60 104.57 109.04 109.65 111.85 115.16 118.27 120.04
 [9,] 102.65 104.95 109.34 109.69 112.16 115.89 119.00 120.52
[10,] 102.74 105.49 109.37 109.91 112.49 116.25 119.33 120.43
[11,] 102.82 106.03 108.96 110.09 112.66 116.43 119.17 120.34
[12,] 103.20 106.48 108.77 110.44 113.39 116.83 119.57 120.75
> 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] 102.2033 104.5917 108.4208 109.4875 111.7658 115.2325 118.2808 120.0558
> arr.sd
[1] 0.7940727 1.0919860 1.0493328 0.6358548 0.9645108 1.1495859 1.0063115
[8] 0.6117108
> arr.range
[1] 2.56 3.73 3.12 2.33 3.49 3.91 3.40 2.13
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   1.326121    -0.003714  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       2.6784        -0.5933  

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

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

Coefficients:
(Intercept)     arr.mean  
   3.486012    -0.003616  

> postscript(file="/var/wessaorg/rcomp/tmp/1bzoa1426192572.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/20di41426192572.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/39mm71426192572.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/46idt1426192572.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5is9t1426192572.tab") 
> 
> try(system("convert tmp/1bzoa1426192572.ps tmp/1bzoa1426192572.png",intern=TRUE))
character(0)
> try(system("convert tmp/20di41426192572.ps tmp/20di41426192572.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.882   0.185   1.066