R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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> x <- c(93.6,103.5,127,117.5,111.5,137.6,103.2,86.9,124.4,113.6,101.6,148.5,108.3,117.2,128.7,116.5,131.7,139.9,107.4,96.1,126.5,116.4,109.8,148,111.4,117,141.7,120,132.1,146.7,122.5,99.6,122.7,139,117.8,125.5,134.5,121.3,126.7,117.7,123,132.1,113.1,89.2,121.7,105.3,85.3,105.3,72.2,92.1,97.2,78.6,78.1,93,81,65.9,88.6,85.7,76.3,96.8,76.8,85.6,119.2,91.4,95.7,112.3,95.2,82.8,111.3,108.2,97,124.4,99.3,117.6,131.5,114.2,116.8,116.5,105.4,89.2,115.8,111.4,106.4,128.4,107.7,111,129.8,130.5,142.9,159.9,84.1,75,100.7,106.8,97.4,113,76.9,87.3,103.7,92.1,92.9,112.2,88.7,74.6,101.5,119.7,120.7,153.5)
> 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,]  93.6 108.3 111.4 134.5 72.2  76.8  99.3 107.7  76.9
 [2,] 103.5 117.2 117.0 121.3 92.1  85.6 117.6 111.0  87.3
 [3,] 127.0 128.7 141.7 126.7 97.2 119.2 131.5 129.8 103.7
 [4,] 117.5 116.5 120.0 117.7 78.6  91.4 114.2 130.5  92.1
 [5,] 111.5 131.7 132.1 123.0 78.1  95.7 116.8 142.9  92.9
 [6,] 137.6 139.9 146.7 132.1 93.0 112.3 116.5 159.9 112.2
 [7,] 103.2 107.4 122.5 113.1 81.0  95.2 105.4  84.1  88.7
 [8,]  86.9  96.1  99.6  89.2 65.9  82.8  89.2  75.0  74.6
 [9,] 124.4 126.5 122.7 121.7 88.6 111.3 115.8 100.7 101.5
[10,] 113.6 116.4 139.0 105.3 85.7 108.2 111.4 106.8 119.7
[11,] 101.6 109.8 117.8  85.3 76.3  97.0 106.4  97.4 120.7
[12,] 148.5 148.0 125.5 105.3 96.8 124.4 128.4 113.0 153.5
> 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] 114.07500 120.54167 124.66667 114.60000  83.79167  99.99167 112.70833
[8] 113.23333 101.98333
> arr.sd
[1] 18.02570 14.87912 13.40830 15.67575 10.03326 15.00348 11.65227 24.16957
[9] 22.10918
> arr.range
[1] 61.6 51.9 47.1 49.2 31.3 47.6 42.3 84.9 78.9
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    8.15106      0.07264  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -0.6765         0.7292  

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

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

Coefficients:
(Intercept)     arr.mean  
    17.8393       0.3391  

> postscript(file="/var/wessaorg/rcomp/tmp/1l8b71426178656.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/2n8521426178656.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/3dcbe1426178657.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4tg2c1426178657.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5py6i1426178657.tab") 
> 
> try(system("convert tmp/1l8b71426178656.ps tmp/1l8b71426178656.png",intern=TRUE))
character(0)
> try(system("convert tmp/2n8521426178656.ps tmp/2n8521426178656.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.868   0.159   1.038