R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(2.27,2.35,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.54,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.66,2.93,2.93,2.93,2.93,2.93,2.93,2.93,2.93,2.93,2.93,2.93,2.93,2.93,3.07,3.07,3.07,3.07,3.07,3.07,3.07,3.07,3.07,3.07)
> 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] 72
> (np <- floor(n / par1))
[1] 6
> 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]
 [1,] 2.27 2.54 2.54 2.66 2.66 2.93
 [2,] 2.35 2.54 2.66 2.66 2.93 2.93
 [3,] 2.54 2.54 2.66 2.66 2.93 3.07
 [4,] 2.54 2.54 2.66 2.66 2.93 3.07
 [5,] 2.54 2.54 2.66 2.66 2.93 3.07
 [6,] 2.54 2.54 2.66 2.66 2.93 3.07
 [7,] 2.54 2.54 2.66 2.66 2.93 3.07
 [8,] 2.54 2.54 2.66 2.66 2.93 3.07
 [9,] 2.54 2.54 2.66 2.66 2.93 3.07
[10,] 2.54 2.54 2.66 2.66 2.93 3.07
[11,] 2.54 2.54 2.66 2.66 2.93 3.07
[12,] 2.54 2.54 2.66 2.66 2.93 3.07
> 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] 2.501667 2.540000 2.650000 2.660000 2.907500 3.046667
> arr.sd
[1] 0.09113759 0.00000000 0.03464102 0.00000000 0.07794229 0.05449493
> arr.range
[1] 0.27 0.00 0.12 0.00 0.27 0.14
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.08320      0.04645  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 
  NA/NaN/Inf in 'y'
Calls: lm -> lm.fit
Execution halted