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(192528,190773,188996,185320,221698,219771,192528,174414,176163,176163,178112,181616,192528,188996,194449,203412,254400,254400,243516,232604,241567,252473,254400,259853,276217,265306,265306,281670,327033,330709,321580,299762,316121,316121,317876,327033,334241,337917,337917,348823,390681,401565,403314,376071,390681,385228,374317,397889,403314,394185,396112,408773,456085,479624,479624,468740,485082,468740,459588,494239,499664,486832,519533,532366,570521,595842,592339,590389,604999,603222,581432,614128,625040,614128,659491,681309,732102,752143,746712,735800,744935,755841,719441,748461,766753,759373,806657,822993,892101,904761,888424,897554,903007,908460,873809,906511,924624,906511,959275,975618,1046468,1057380,1060884,1079170,1079170,1086378,1053676,1070041,1080925,1060884,1119079,1129986,1202597,1215430,1233543,1249908,1251657,1253584,1220883,1253584)
> 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]   [,10]
 [1,] 192528 192528 276217 334241 403314 499664 625040 766753  924624 1080925
 [2,] 190773 188996 265306 337917 394185 486832 614128 759373  906511 1060884
 [3,] 188996 194449 265306 337917 396112 519533 659491 806657  959275 1119079
 [4,] 185320 203412 281670 348823 408773 532366 681309 822993  975618 1129986
 [5,] 221698 254400 327033 390681 456085 570521 732102 892101 1046468 1202597
 [6,] 219771 254400 330709 401565 479624 595842 752143 904761 1057380 1215430
 [7,] 192528 243516 321580 403314 479624 592339 746712 888424 1060884 1233543
 [8,] 174414 232604 299762 376071 468740 590389 735800 897554 1079170 1249908
 [9,] 176163 241567 316121 390681 485082 604999 744935 903007 1079170 1251657
[10,] 176163 252473 316121 385228 468740 603222 755841 908460 1086378 1253584
[11,] 178112 254400 317876 374317 459588 581432 719441 873809 1053676 1220883
[12,] 181616 259853 327033 397889 494239 614128 748461 906511 1070041 1253584
> 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]  189840.2  231049.8  303727.8  373220.3  449508.8  565938.9  709616.9
 [8]  860866.9 1024932.9 1189338.3
> arr.sd
 [1] 15853.08 27877.37 24957.95 26437.10 37743.05 44332.24 51301.59 56271.22
 [9] 64777.47 71558.01
> arr.range
 [1]  47284  70857  65403  69073 100054 127296 141713 149087 179867 192700
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  1.086e+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)  
       0.7564         0.7465  

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

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

Coefficients:
(Intercept)     arr.mean  
  2.863e+04    1.453e-01  

> postscript(file="/var/wessaorg/rcomp/tmp/1iulv1409236970.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/27pxp1409236970.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/3iuu81409236970.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4rulx1409236970.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5ob971409236970.tab") 
> 
> try(system("convert tmp/1iulv1409236970.ps tmp/1iulv1409236970.png",intern=TRUE))
character(0)
> try(system("convert tmp/27pxp1409236970.ps tmp/27pxp1409236970.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.886   0.152   1.046