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(865911,858030,850038,833499,997113,988455,865911,784437,792318,792318,801087,816849,865911,850038,874569,914862,1144188,1144188,1095237,1046175,1086468,1135530,1144188,1168719,1242312,1193250,1193250,1266843,1470861,1487400,1446330,1348206,1421799,1421799,1429680,1470861,1503273,1519812,1519812,1568874,1757130,1806081,1813962,1691418,1757130,1732599,1683537,1789542,1813962,1772892,1781550,1838493,2051280,2157174,2157174,2108223,2181705,2108223,2067042,2222886,2247306,2189586,2336661,2394381,2565987,2679873,2664111,2655342,2721054,2713062,2615049,2762124,2811186,2762124,2966142,3064266,3292704,3382836,3358416,3309354,3350424,3399486,3235761,3366297,3448548,3415359,3628035,3701517,4012317,4069260,3995778,4036848,4061379,4085910,3930066,4077141,4158615,4077141,4314459,4387941,4706622,4755684,4771446,4853697,4853697,4886109,4739034,4812627,4861578,4771446,5033184,5082246,5408808,5466528,5548002,5621595,5629476,5638134,5491059,5638134)
> 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,] 865911  865911 1242312 1503273 1813962 2247306 2811186 3448548 4158615
 [2,] 858030  850038 1193250 1519812 1772892 2189586 2762124 3415359 4077141
 [3,] 850038  874569 1193250 1519812 1781550 2336661 2966142 3628035 4314459
 [4,] 833499  914862 1266843 1568874 1838493 2394381 3064266 3701517 4387941
 [5,] 997113 1144188 1470861 1757130 2051280 2565987 3292704 4012317 4706622
 [6,] 988455 1144188 1487400 1806081 2157174 2679873 3382836 4069260 4755684
 [7,] 865911 1095237 1446330 1813962 2157174 2664111 3358416 3995778 4771446
 [8,] 784437 1046175 1348206 1691418 2108223 2655342 3309354 4036848 4853697
 [9,] 792318 1086468 1421799 1757130 2181705 2721054 3350424 4061379 4853697
[10,] 792318 1135530 1421799 1732599 2108223 2713062 3399486 4085910 4886109
[11,] 801087 1144188 1429680 1683537 2067042 2615049 3235761 3930066 4739034
[12,] 816849 1168719 1470861 1789542 2222886 2762124 3366297 4077141 4812627
        [,10]
 [1,] 4861578
 [2,] 4771446
 [3,] 5033184
 [4,] 5082246
 [5,] 5408808
 [6,] 5466528
 [7,] 5548002
 [8,] 5621595
 [9,] 5629476
[10,] 5638134
[11,] 5491059
[12,] 5638134
> 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]  853830.5 1039172.8 1366049.2 1678597.5 2021717.0 2545378.0 3191583.0
 [8] 3871846.5 4609756.0 5349182.5
> arr.sd
 [1]  71301.82 125379.34 112248.62 118906.95 169755.03 199388.58 230731.52
 [8] 253087.89 291342.61 321839.88
> arr.range
 [1] 212676 318681 294150 310689 449994 572538 637362 670551 808968 866688
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  4.883e+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)  
       1.1376         0.7465  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.288e+05    1.453e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/15d951377070484.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/2bxr71377070484.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/3xvns1377070484.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4idjn1377070484.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/52vsr1377070485.tab") 
> 
> try(system("convert tmp/15d951377070484.ps tmp/15d951377070484.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bxr71377070484.ps tmp/2bxr71377070484.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.482   0.394   1.855