R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> x <- c(2421.21,2378.63,2336.00,2250.79,3113.00,3070.38,2421.21,1990.13,2032.71,2032.71,2075.33,2165.17,1904.92,1644.25,1430.79,1430.79,2250.79,2336.00,1686.83,952.46,1340.96,1340.96,1644.25,1819.29,1776.67,1340.96,1559.04,1473.42,2207.79,2032.71,1340.96,824.25,1298.33,1430.79,1559.04,1729.46,1383.54,1084.92,1213.17,1255.75,2378.63,2378.63,1729.46,1644.25,1904.92,1776.67,2122.58,2553.67,2639.29,2032.71,1861.88,1686.83,2856.96,2942.58,2724.50,2942.58,2899.54,2553.67,2942.58,3373.67,3548.71,3027.79,2681.88,2942.58,4065.42,4411.33,4326.13,4496.50,4453.92,4022.83,4757.21,4932.25,5188.29,4411.33,4108.04,4453.92,5278.13,6012.50,5837.46,5837.46,5923.08,5624.00,6401.42,6401.42,6268.96,5534.17,5666.63,5752.25,6315.79,7050.17,6529.21,6789.92,6571.83,6444.00,7439.08,7221.00,6917.71,6486.63,6917.71,7135.79,7396.04,7741.92,7396.04,7609.50,7349.21,7306.63,8386.88,8476.71,8130.83,7524.29,8041.00,8258.67,8519.33,8907.83,8519.33,8822.63,8690.17,8216.04,9211.08,9211.08)
> 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]
 [1,] 2421.21 1904.92 1776.67 1383.54 2639.29 3548.71 5188.29 6268.96 6917.71
 [2,] 2378.63 1644.25 1340.96 1084.92 2032.71 3027.79 4411.33 5534.17 6486.63
 [3,] 2336.00 1430.79 1559.04 1213.17 1861.88 2681.88 4108.04 5666.63 6917.71
 [4,] 2250.79 1430.79 1473.42 1255.75 1686.83 2942.58 4453.92 5752.25 7135.79
 [5,] 3113.00 2250.79 2207.79 2378.63 2856.96 4065.42 5278.13 6315.79 7396.04
 [6,] 3070.38 2336.00 2032.71 2378.63 2942.58 4411.33 6012.50 7050.17 7741.92
 [7,] 2421.21 1686.83 1340.96 1729.46 2724.50 4326.13 5837.46 6529.21 7396.04
 [8,] 1990.13  952.46  824.25 1644.25 2942.58 4496.50 5837.46 6789.92 7609.50
 [9,] 2032.71 1340.96 1298.33 1904.92 2899.54 4453.92 5923.08 6571.83 7349.21
[10,] 2032.71 1340.96 1430.79 1776.67 2553.67 4022.83 5624.00 6444.00 7306.63
[11,] 2075.33 1644.25 1559.04 2122.58 2942.58 4757.21 6401.42 7439.08 8386.88
[12,] 2165.17 1819.29 1729.46 2553.67 3373.67 4932.25 6401.42 7221.00 8476.71
        [,10]
 [1,] 8130.83
 [2,] 7524.29
 [3,] 8041.00
 [4,] 8258.67
 [5,] 8519.33
 [6,] 8907.83
 [7,] 8519.33
 [8,] 8822.63
 [9,] 8690.17
[10,] 8216.04
[11,] 9211.08
[12,] 9211.08
> 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] 2357.273 1648.524 1547.785 1785.516 2621.399 3972.213 5456.421 6465.251
 [9] 7426.731 8504.357
> arr.sd
 [1] 376.8216 393.1532 362.6804 495.9221 506.3789 748.9710 777.5569 607.2956
 [9] 577.3017 500.5651
> arr.range
 [1] 1122.87 1383.54 1383.54 1468.75 1686.84 2250.37 2293.38 1904.91 1990.08
[10] 1686.79
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   421.0161       0.0272  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       4.0667         0.2678  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.357e+03    8.623e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/1nr4o1470741933.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/2lpa41470741933.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/3c6q01470741933.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4prr61470741933.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5uwvs1470741933.tab") 
> 
> try(system("convert tmp/1nr4o1470741933.ps tmp/1nr4o1470741933.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lpa41470741933.ps tmp/2lpa41470741933.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.886   0.102   0.990