R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(58109,57087,56064,54019,74712,73689,58109,47763,48785,48785,49808,51964,45718,39462,34339,34339,54019,56064,40484,22859,32183,32183,39462,43663,42640,32183,37417,35362,52987,48785,32183,19782,31160,34339,37417,41507,33205,26038,29116,30138,57087,57087,41507,39462,45718,42640,50942,61288,63343,48785,44685,40484,68567,70622,65388,70622,69589,61288,70622,80968,85169,72667,64365,70622,97570,105872,103827,107916,106894,96548,114173,118374,124519,105872,98593,106894,126675,144300,140099,140099,142154,134976,153634,153634,150455,132820,135999,138054,151579,169204,156701,162958,157724,154656,178538,173304,166025,155679,166025,171259,177505,185806,177505,182628,176381,175359,201285,203441,195140,180583,192984,198208,204464,213788,204464,211743,208564,197185,221066,221066)
> 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,] 58109 45718 42640 33205 63343  85169 124519 150455 166025 195140
 [2,] 57087 39462 32183 26038 48785  72667 105872 132820 155679 180583
 [3,] 56064 34339 37417 29116 44685  64365  98593 135999 166025 192984
 [4,] 54019 34339 35362 30138 40484  70622 106894 138054 171259 198208
 [5,] 74712 54019 52987 57087 68567  97570 126675 151579 177505 204464
 [6,] 73689 56064 48785 57087 70622 105872 144300 169204 185806 213788
 [7,] 58109 40484 32183 41507 65388 103827 140099 156701 177505 204464
 [8,] 47763 22859 19782 39462 70622 107916 140099 162958 182628 211743
 [9,] 48785 32183 31160 45718 69589 106894 142154 157724 176381 208564
[10,] 48785 32183 34339 42640 61288  96548 134976 154656 175359 197185
[11,] 49808 39462 37417 50942 70622 114173 153634 178538 201285 221066
[12,] 51964 43663 41507 61288 80968 118374 153634 173304 203441 221066
> 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]  56574.50  39564.58  37146.83  42852.33  62913.58  95333.08 130954.08
 [8] 155166.00 178241.50 204104.58
> arr.sd
 [1]  9043.710  9435.688  8704.326 11902.114 12153.104 17975.301 18661.343
 [8] 14575.122 13855.236 12013.570
> arr.range
 [1] 26949 33205 33205 35250 40484 54009 55041 45718 47762 40483
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   1.01e+04     2.72e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       6.3938         0.2678  

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

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

Coefficients:
(Intercept)     arr.mean  
  3.256e+04    8.623e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/1rh101471216859.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/2fa0u1471216859.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/3qynm1471216859.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4da4r1471216859.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5bgu21471216859.tab") 
> 
> try(system("convert tmp/1rh101471216859.ps tmp/1rh101471216859.png",intern=TRUE))
character(0)
> try(system("convert tmp/2fa0u1471216859.ps tmp/2fa0u1471216859.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.892   0.082   0.983