R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(1155168,1144638,1133976,1111920,1330188,1318626,1155168,1046484,1056978,1056978,1068672,1089696,1155168,1133976,1166694,1220472,1526400,1526400,1461096,1395624,1449402,1514838,1526400,1559118,1657302,1591836,1591836,1690020,1962198,1984254,1929480,1798572,1896726,1896726,1907256,1962198,2005446,2027502,2027502,2092938,2344086,2409390,2419884,2256426,2344086,2311368,2245902,2387334,2419884,2365110,2376672,2452638,2736510,2877744,2877744,2812440,2910492,2812440,2757528,2965434,2997984,2920992,3117198,3194196,3423126,3575052,3554034,3542334,3629994,3619332,3488592,3684768,3750240,3684768,3956946,4087854,4392612,4512858,4480272,4414800,4469610,4535046,4316646,4490766,4600518,4556238,4839942,4937958,5352606,5428566,5330544,5385324,5418042,5450760,5242854,5439066,5547744,5439066,5755650,5853708,6278808,6344280,6365304,6475020,6475020,6518268,6322056,6420246,6485550,6365304,6714474,6779916,7215582,7292580,7401258,7499448,7509942,7521504,7325298,7521504)
> 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,] 1155168 1155168 1657302 2005446 2419884 2997984 3750240 4600518 5547744
 [2,] 1144638 1133976 1591836 2027502 2365110 2920992 3684768 4556238 5439066
 [3,] 1133976 1166694 1591836 2027502 2376672 3117198 3956946 4839942 5755650
 [4,] 1111920 1220472 1690020 2092938 2452638 3194196 4087854 4937958 5853708
 [5,] 1330188 1526400 1962198 2344086 2736510 3423126 4392612 5352606 6278808
 [6,] 1318626 1526400 1984254 2409390 2877744 3575052 4512858 5428566 6344280
 [7,] 1155168 1461096 1929480 2419884 2877744 3554034 4480272 5330544 6365304
 [8,] 1046484 1395624 1798572 2256426 2812440 3542334 4414800 5385324 6475020
 [9,] 1056978 1449402 1896726 2344086 2910492 3629994 4469610 5418042 6475020
[10,] 1056978 1514838 1896726 2311368 2812440 3619332 4535046 5450760 6518268
[11,] 1068672 1526400 1907256 2245902 2757528 3488592 4316646 5242854 6322056
[12,] 1089696 1559118 1962198 2387334 2965434 3684768 4490766 5439066 6420246
        [,10]
 [1,] 6485550
 [2,] 6365304
 [3,] 6714474
 [4,] 6779916
 [5,] 7215582
 [6,] 7292580
 [7,] 7401258
 [8,] 7499448
 [9,] 7509942
[10,] 7521504
[11,] 7325298
[12,] 7521504
> 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] 1139041 1386299 1822367 2239322 2697053 3395634 4257702 5165202 6149598
[10] 7136030
> arr.sd
 [1]  95118.51 167264.21 149747.71 158622.61 226458.29 265993.43 307809.56
 [8] 337627.33 388664.83 429348.06
> arr.range
 [1]  283704  425142  392418  414438  600324  763776  850278  894522 1079202
[10] 1156200
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  6.514e+04    5.299e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       1.2107         0.7465  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.718e+05    1.453e-01  

> postscript(file="/var/fisher/rcomp/tmp/1i1bi1373033557.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/fisher/rcomp/tmp/25fn31373033557.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/3td941373033557.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/46gek1373033557.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/fisher/rcomp/tmp/5ae6a1373033557.tab") 
> 
> try(system("convert tmp/1i1bi1373033557.ps tmp/1i1bi1373033557.png",intern=TRUE))
character(0)
> try(system("convert tmp/25fn31373033557.ps tmp/25fn31373033557.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.612   0.435   2.020