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(-6,-3,-2,-5,-11,-11,-11,-10,-14,-8,-9,-5,-1,-2,-5,-4,-6,-2,-2,-2,-2,2,1,-8,-1,1,-1,2,2,1,-1,-2,-2,-1,-8,-4,-6,-3,-3,-7,-9,-11,-13,-11,-9,-17,-22,-25,-20,-24,-24,-22,-19,-18,-17,-11,-11,-12,-10,-15,-15,-15,-13,-8,-13,-9,-7,-4,-4,-2,0,-2)
> 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,]   -6   -1   -1   -6  -20  -15
 [2,]   -3   -2    1   -3  -24  -15
 [3,]   -2   -5   -1   -3  -24  -13
 [4,]   -5   -4    2   -7  -22   -8
 [5,]  -11   -6    2   -9  -19  -13
 [6,]  -11   -2    1  -11  -18   -9
 [7,]  -11   -2   -1  -13  -17   -7
 [8,]  -10   -2   -2  -11  -11   -4
 [9,]  -14   -2   -2   -9  -11   -4
[10,]   -8    2   -1  -17  -12   -2
[11,]   -9    1   -8  -22  -10    0
[12,]   -5   -8   -4  -25  -15   -2
> 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]  -7.916667  -2.583333  -1.166667 -11.333333 -16.916667  -7.666667
> arr.sd
[1] 3.704011 2.810963 2.790677 6.958753 5.107184 5.365434
> arr.range
[1] 12 10 10 22 14 15
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
     2.8296      -0.2051  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 
  0 (non-NA) cases
Calls: lm -> lm.fit
In addition: Warning message:
In log(arr.mean) : NaNs produced
Execution halted