R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(6195800,6172725,6149325,6100900,6579950,6554600,6195800,5957250,5980325,5980325,6006000,6052150,6123975,6123975,6077825,5957250,6579950,6674850,6531525,6195800,6339450,6123975,6221150,6267625,6316050,6195800,6221150,6052150,6579950,6746675,6603350,6339450,6626425,6316050,6603350,6579950,6651775,6387875,6674850,6651775,7082400,6985225,6603350,6410950,6674850,6316050,6579950,6626425,6723600,6508450,6626425,6698250,6962150,6746675,6459700,6149325,6436625,5646875,6029075,6244225,6459700,6149325,6149325,6149325,6316050,6077825,5765175,5503550,5693350,4952350,5406375,5670275,5718700,5454800,5477875,5406375,5646875,5477875,5144750,4903925,5311150,4426825,5001100,5262725,5262725,4952350,4665375,4642300,4903925,4665375,4211675,3899025,4234750,3445325,4162925,4544800,4665375,4401475,4068025,4306575,4401475,4329650,3611725,3278600,3516825,2799225,3540225,3804125,4019275,3660475,3324750,3516825,3611725,3421925,2704325,2391675,2678650,1889225,2750475,3278600)
> 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,] 6195800 6123975 6316050 6651775 6723600 6459700 5718700 5262725 4665375
 [2,] 6172725 6123975 6195800 6387875 6508450 6149325 5454800 4952350 4401475
 [3,] 6149325 6077825 6221150 6674850 6626425 6149325 5477875 4665375 4068025
 [4,] 6100900 5957250 6052150 6651775 6698250 6149325 5406375 4642300 4306575
 [5,] 6579950 6579950 6579950 7082400 6962150 6316050 5646875 4903925 4401475
 [6,] 6554600 6674850 6746675 6985225 6746675 6077825 5477875 4665375 4329650
 [7,] 6195800 6531525 6603350 6603350 6459700 5765175 5144750 4211675 3611725
 [8,] 5957250 6195800 6339450 6410950 6149325 5503550 4903925 3899025 3278600
 [9,] 5980325 6339450 6626425 6674850 6436625 5693350 5311150 4234750 3516825
[10,] 5980325 6123975 6316050 6316050 5646875 4952350 4426825 3445325 2799225
[11,] 6006000 6221150 6603350 6579950 6029075 5406375 5001100 4162925 3540225
[12,] 6052150 6267625 6579950 6626425 6244225 5670275 5262725 4544800 3804125
        [,10]
 [1,] 4019275
 [2,] 3660475
 [3,] 3324750
 [4,] 3516825
 [5,] 3611725
 [6,] 3421925
 [7,] 2704325
 [8,] 2391675
 [9,] 2678650
[10,] 1889225
[11,] 2750475
[12,] 3278600
> 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] 6160429 6268112 6431696 6637123 6435948 5857719 5269415 4465879 3893608
[10] 3103994
> arr.sd
 [1] 208766.6 221515.4 217278.4 222304.7 366082.5 436468.7 358941.8 500284.2
 [9] 558634.5 618254.3
> arr.range
 [1]  622700  717600  694525  766350 1315275 1507350 1291875 1817400 1866150
[10] 2130050
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  9.878e+05   -1.132e-01  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       34.203         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
  3.444e+06   -3.983e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1xfmk1439579100.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/2txmh1439579100.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/3f8pi1439579100.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4i7gp1439579100.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5tkjd1439579100.tab") 
> 
> try(system("convert tmp/1xfmk1439579100.ps tmp/1xfmk1439579100.png",intern=TRUE))
character(0)
> try(system("convert tmp/2txmh1439579100.ps tmp/2txmh1439579100.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.012   0.206   1.218