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(5452304,5431998,5411406,5368792,5790356,5768048,5452304,5242380,5262686,5262686,5285280,5325892,5389098,5389098,5348486,5242380,5790356,5873868,5747742,5452304,5578716,5389098,5474612,5515510,5558124,5452304,5474612,5325892,5790356,5937074,5810948,5578716,5831254,5558124,5810948,5790356,5853562,5621330,5873868,5853562,6232512,6146998,5810948,5641636,5873868,5558124,5790356,5831254,5916768,5727436,5831254,5894460,6126692,5937074,5684536,5411406,5664230,4969250,5305586,5494918,5684536,5411406,5411406,5411406,5558124,5348486,5073354,4843124,5010148,4358068,4757610,4989842,5032456,4800224,4820530,4757610,4969250,4820530,4527380,4315454,4673812,3895606,4400968,4631198,4631198,4358068,4105530,4085224,4315454,4105530,3706274,3431142,3726580,3031886,3663374,3999424,4105530,3873298,3579862,3789786,3873298,3810092,3178318,2885168,3094806,2463318,3115398,3347630,3536962,3221218,2925780,3094806,3178318,3011294,2379806,2104674,2357212,1662518,2420418,2885168)
> 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,] 5452304 5389098 5558124 5853562 5916768 5684536 5032456 4631198 4105530
 [2,] 5431998 5389098 5452304 5621330 5727436 5411406 4800224 4358068 3873298
 [3,] 5411406 5348486 5474612 5873868 5831254 5411406 4820530 4105530 3579862
 [4,] 5368792 5242380 5325892 5853562 5894460 5411406 4757610 4085224 3789786
 [5,] 5790356 5790356 5790356 6232512 6126692 5558124 4969250 4315454 3873298
 [6,] 5768048 5873868 5937074 6146998 5937074 5348486 4820530 4105530 3810092
 [7,] 5452304 5747742 5810948 5810948 5684536 5073354 4527380 3706274 3178318
 [8,] 5242380 5452304 5578716 5641636 5411406 4843124 4315454 3431142 2885168
 [9,] 5262686 5578716 5831254 5873868 5664230 5010148 4673812 3726580 3094806
[10,] 5262686 5389098 5558124 5558124 4969250 4358068 3895606 3031886 2463318
[11,] 5285280 5474612 5810948 5790356 5305586 4757610 4400968 3663374 3115398
[12,] 5325892 5515510 5790356 5831254 5494918 4989842 4631198 3999424 3347630
        [,10]
 [1,] 3536962
 [2,] 3221218
 [3,] 2925780
 [4,] 3094806
 [5,] 3178318
 [6,] 3011294
 [7,] 2379806
 [8,] 2104674
 [9,] 2357212
[10,] 1662518
[11,] 2420418
[12,] 2885168
> 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] 5421178 5515939 5659892 5840668 5663634 5154792 4637085 3929974 3426375
[10] 2731514
> arr.sd
 [1] 183714.6 194933.5 191205.0 195628.1 322152.6 384092.5 315868.8 440250.1
 [9] 491598.3 544063.8
> arr.range
 [1]  547976  631488  611182  674388 1157442 1326468 1136850 1599312 1642212
[10] 1874444
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  8.693e+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)  
       33.898         -1.386  

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

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

Coefficients:
(Intercept)     arr.mean  
  3.031e+06   -3.983e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1t29q1439679698.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/2c2k41439679698.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/3k87d1439679698.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4e8do1439679698.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5i7851439679698.tab") 
> 
> try(system("convert tmp/1t29q1439679698.ps tmp/1t29q1439679698.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c2k41439679698.ps tmp/2c2k41439679698.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.919   0.118   1.037