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(1069108,1059362,1049495,1029082,1231089,1220388,1069108,968521,978233,978233,989056,1008514,1069108,1049495,1079775,1129547,1412683,1412683,1352244,1291650,1341422,1401983,1412683,1442964,1533833,1473244,1473244,1564114,1816014,1836427,1785734,1664578,1755420,1755420,1765165,1816014,1856040,1876453,1876453,1937014,2169452,2229890,2239603,2088322,2169452,2139171,2078582,2209478,2239603,2188909,2199610,2269916,2532640,2663352,2663352,2602913,2693660,2602913,2552092,2744509,2774634,2703378,2884967,2956228,3168103,3308711,3289258,3278430,3359559,3349692,3228692,3410253,3470847,3410253,3662154,3783309,4065362,4176650,4146492,4085897,4136624,4197185,3995056,4156204,4257779,4216798,4479366,4570080,4953837,5024138,4933418,4984117,5014398,5044678,4852261,5033856,5134437,5033856,5326854,5417607,5811037,5871631,5891089,5992631,5992631,6032657,5851063,5941938,6002377,5891089,6214246,6274812,6678021,6749283,6849864,6940739,6950451,6961152,6779563,6961152)
> 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,] 1069108 1069108 1533833 1856040 2239603 2774634 3470847 4257779 5134437
 [2,] 1059362 1049495 1473244 1876453 2188909 2703378 3410253 4216798 5033856
 [3,] 1049495 1079775 1473244 1876453 2199610 2884967 3662154 4479366 5326854
 [4,] 1029082 1129547 1564114 1937014 2269916 2956228 3783309 4570080 5417607
 [5,] 1231089 1412683 1816014 2169452 2532640 3168103 4065362 4953837 5811037
 [6,] 1220388 1412683 1836427 2229890 2663352 3308711 4176650 5024138 5871631
 [7,] 1069108 1352244 1785734 2239603 2663352 3289258 4146492 4933418 5891089
 [8,]  968521 1291650 1664578 2088322 2602913 3278430 4085897 4984117 5992631
 [9,]  978233 1341422 1755420 2169452 2693660 3359559 4136624 5014398 5992631
[10,]  978233 1401983 1755420 2139171 2602913 3349692 4197185 5044678 6032657
[11,]  989056 1412683 1765165 2078582 2552092 3228692 3995056 4852261 5851063
[12,] 1008514 1442964 1816014 2209478 2744509 3410253 4156204 5033856 5941938
        [,10]
 [1,] 6002377
 [2,] 5891089
 [3,] 6214246
 [4,] 6274812
 [5,] 6678021
 [6,] 6749283
 [7,] 6849864
 [8,] 6940739
 [9,] 6950451
[10,] 6961152
[11,] 6779563
[12,] 6961152
> 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] 1054182 1283020 1686601 2072492 2496122 3142659 3940503 4780394 5691453
[10] 6604396
> arr.sd
 [1]  88032.11 154803.03 138591.49 146805.36 209587.10 246176.96 284877.65
 [8] 312474.22 359709.27 397361.49
> arr.range
 [1]  262568  393469  363183  383563  555600  706875  786932  827880  998801
[10] 1070063
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  6.029e+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)  
       1.1911         0.7465  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.590e+05    1.453e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1lagf1404903196.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/2lcnj1404903196.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/3sqk51404903196.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4stk11404903196.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5uuqj1404903196.tab") 
> 
> try(system("convert tmp/1lagf1404903196.ps tmp/1lagf1404903196.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lcnj1404903196.ps tmp/2lcnj1404903196.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.902   0.152   1.040