R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(58896,57616,56232,53708,79784,78524,58896,45848,47112,47112,48372,51040,54968,53708,45848,47112,83716,91572,70664,58896,61548,62828,69404,75856,77260,64088,65476,48372,96888,111200,78524,68016,74596,82452,94220,108656,108656,99412,95484,71928,111200,129564,113848,96888,99412,108656,121704,137420,126896,120444,120444,99412,129564,149188,133492,116516,121704,142612,151856,164888,154380,137420,133492,102080,122968,145260,120444,106008,120444,134756,142612,163624,153120,126896,129564,104744,125636,144000,122968,108656,121704,137420,134756,166168,160976,140068,141332,113848,130824,157048,137420,125636,145260,157048,147928,189724,179340,155784,149188,119056,136140,151856,132212,132212,154380,166168,159696,205420,193652,171484,162240,129564,141332,162240,146524,142612,160976,176672,159696,200228)
> 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] 120
> (np <- floor(n / par1))
[1] 10
> 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]  [,10]
 [1,] 58896 54968  77260 108656 126896 154380 153120 160976 179340 193652
 [2,] 57616 53708  64088  99412 120444 137420 126896 140068 155784 171484
 [3,] 56232 45848  65476  95484 120444 133492 129564 141332 149188 162240
 [4,] 53708 47112  48372  71928  99412 102080 104744 113848 119056 129564
 [5,] 79784 83716  96888 111200 129564 122968 125636 130824 136140 141332
 [6,] 78524 91572 111200 129564 149188 145260 144000 157048 151856 162240
 [7,] 58896 70664  78524 113848 133492 120444 122968 137420 132212 146524
 [8,] 45848 58896  68016  96888 116516 106008 108656 125636 132212 142612
 [9,] 47112 61548  74596  99412 121704 120444 121704 145260 154380 160976
[10,] 47112 62828  82452 108656 142612 134756 137420 157048 166168 176672
[11,] 48372 69404  94220 121704 151856 142612 134756 147928 159696 159696
[12,] 51040 75856 108656 137420 164888 163624 166168 189724 205420 200228
> 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]  56928.33  64676.67  80812.33 107847.67 131418.00 131957.33 131302.67
 [8] 145592.67 153454.33 162268.33
> arr.sd
 [1] 11406.55 14120.45 18894.65 17299.99 18062.75 18458.82 17416.15 19521.10
 [9] 23323.10 21038.30
> arr.range
 [1] 33936 45724 62828 65492 65476 61544 61424 75876 86364 70664
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  9.164e+03    7.537e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       4.3394         0.4685  

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

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

Coefficients:
(Intercept)     arr.mean  
  2.405e+04    3.334e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/19s651377054652.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/2qihq1377054652.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/3nall1377054652.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4rcb01377054652.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5dxew1377054652.tab") 
> 
> try(system("convert tmp/19s651377054652.ps tmp/19s651377054652.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qihq1377054652.ps tmp/2qihq1377054652.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.084   0.546   2.596