R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(7175,7049,6923,6670,9225,9099,7175,5898,6024,6024,6150,6416,5645,4873,4240,4240,6670,6923,4999,2823,3974,3974,4873,5391,5265,3974,4620,4366,6543,6024,3974,2443,3848,4240,4620,5125,4100,3215,3595,3721,7049,7049,5125,4873,5645,5265,6290,7568,7821,6024,5518,4999,8466,8720,8074,8720,8593,7568,8720,9998,10516,8973,7948,8720,12048,13073,12820,13325,13199,11921,14098,14616,15375,13073,12174,13199,15641,17818,17299,17299,17553,16666,18970,18970,18578,16400,16793,17046,18716,20893,19349,20121,19475,19096,22045,21399,20500,19223,20500,21146,21918,22943,21918,22550,21779,21653,24854,25120,24095,22298,23829,24474,25246,26398,25246,26145,25753,24348,27296,27296)
> 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,] 7175 5645 5265 4100 7821 10516 15375 18578 20500 24095
 [2,] 7049 4873 3974 3215 6024  8973 13073 16400 19223 22298
 [3,] 6923 4240 4620 3595 5518  7948 12174 16793 20500 23829
 [4,] 6670 4240 4366 3721 4999  8720 13199 17046 21146 24474
 [5,] 9225 6670 6543 7049 8466 12048 15641 18716 21918 25246
 [6,] 9099 6923 6024 7049 8720 13073 17818 20893 22943 26398
 [7,] 7175 4999 3974 5125 8074 12820 17299 19349 21918 25246
 [8,] 5898 2823 2443 4873 8720 13325 17299 20121 22550 26145
 [9,] 6024 3974 3848 5645 8593 13199 17553 19475 21779 25753
[10,] 6024 3974 4240 5265 7568 11921 16666 19096 21653 24348
[11,] 6150 4873 4620 6290 8720 14098 18970 22045 24854 27296
[12,] 6416 5391 5125 7568 9998 14616 18970 21399 25120 27296
> 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]  6985.667  4885.417  4586.833  5291.250  7768.417 11771.417 16169.750
 [8] 19159.250 22008.667 25202.000
> arr.sd
 [1] 1116.633 1165.033 1074.745 1469.746 1500.530 2219.452 2304.186 1799.680
 [9] 1710.776 1483.237
> arr.range
 [1] 3327 4100 4100 4353 4999 6668 6796 5645 5897 4998
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  1.248e+03    2.719e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       4.8623         0.2677  

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

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

Coefficients:
(Intercept)     arr.mean  
  4020.8403       0.0862  

> postscript(file="/var/wessaorg/rcomp/tmp/19n7d1345129674.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/25aev1345129674.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/37kku1345129674.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/43iad1345129674.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5ix2j1345129674.tab") 
> 
> try(system("convert tmp/19n7d1345129674.ps tmp/19n7d1345129674.png",intern=TRUE))
character(0)
> try(system("convert tmp/25aev1345129674.ps tmp/25aev1345129674.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.848   0.177   1.013