R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(7175,7048.75,6922.5,6670,9225,9098.75,7175,5897.5,6023.75,6023.75,6150,6416.25,5645,4872.5,4240,4240,6670,6922.5,4998.75,2822.5,3973.75,3973.75,4872.5,5391.25,5265,3973.75,4620,4366.25,6542.5,6023.75,3973.75,2442.5,3847.5,4240,4620,5125,4100,3215,3595,3721.25,7048.75,7048.75,5125,4872.5,5645,5265,6290,7567.5,7821.25,6023.75,5517.5,4998.75,8466.25,8720,8073.75,8720,8592.5,7567.5,8720,9997.5,10516.25,8972.5,7947.5,8720,12047.5,13072.5,12820,13325,13198.75,11921.25,14097.5,14616.25,15375,13072.5,12173.75,13198.75,15641.25,17817.5,17298.75,17298.75,17552.5,16666.25,18970,18970,18577.5,16400,16792.5,17046.25,18716.25,20892.5,19348.75,20121.25,19475,19096.25,22045,21398.75,20500,19222.5,20500,21146.25,21917.5,22942.5,21917.5,22550,21778.75,21652.5,24853.75,25120,24095,22297.5,23828.75,24473.75,25246.25,26397.5,25246.25,26145,25752.5,24347.5,27296.25,27296.25)
> 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]
 [1,] 7175.00 5645.00 5265.00 4100.00 7821.25 10516.25 15375.00 18577.50
 [2,] 7048.75 4872.50 3973.75 3215.00 6023.75  8972.50 13072.50 16400.00
 [3,] 6922.50 4240.00 4620.00 3595.00 5517.50  7947.50 12173.75 16792.50
 [4,] 6670.00 4240.00 4366.25 3721.25 4998.75  8720.00 13198.75 17046.25
 [5,] 9225.00 6670.00 6542.50 7048.75 8466.25 12047.50 15641.25 18716.25
 [6,] 9098.75 6922.50 6023.75 7048.75 8720.00 13072.50 17817.50 20892.50
 [7,] 7175.00 4998.75 3973.75 5125.00 8073.75 12820.00 17298.75 19348.75
 [8,] 5897.50 2822.50 2442.50 4872.50 8720.00 13325.00 17298.75 20121.25
 [9,] 6023.75 3973.75 3847.50 5645.00 8592.50 13198.75 17552.50 19475.00
[10,] 6023.75 3973.75 4240.00 5265.00 7567.50 11921.25 16666.25 19096.25
[11,] 6150.00 4872.50 4620.00 6290.00 8720.00 14097.50 18970.00 22045.00
[12,] 6416.25 5391.25 5125.00 7567.50 9997.50 14616.25 18970.00 21398.75
          [,9]    [,10]
 [1,] 20500.00 24095.00
 [2,] 19222.50 22297.50
 [3,] 20500.00 23828.75
 [4,] 21146.25 24473.75
 [5,] 21917.50 25246.25
 [6,] 22942.50 26397.50
 [7,] 21917.50 25246.25
 [8,] 22550.00 26145.00
 [9,] 21778.75 25752.50
[10,] 21652.50 24347.50
[11,] 24853.75 27296.25
[12,] 25120.00 27296.25
> 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]  6985.521  4885.208  4586.667  5291.146  7768.229 11771.250 16169.583
 [8] 19159.167 22008.438 25201.875
> arr.sd
 [1] 1116.663 1165.078 1074.776 1469.610 1500.586 2219.511 2304.234 1799.659
 [9] 1710.793 1483.396
> arr.range
 [1] 3327.50 4100.00 4100.00 4352.50 4998.75 6668.75 6796.25 5645.00 5897.50
[10] 4998.75
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  1247.6333       0.0272  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       4.8622         0.2678  

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

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

Coefficients:
(Intercept)     arr.mean  
  4.021e+03    8.624e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/1fsvv1470866443.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/2jfsb1470866443.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/3m8l51470866443.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4s69k1470866443.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5hygh1470866443.tab") 
> 
> try(system("convert tmp/1fsvv1470866443.ps tmp/1fsvv1470866443.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jfsb1470866443.ps tmp/2jfsb1470866443.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.862   0.102   0.967