R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(-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,-3,1,-2,-1,1,-3,-4,-9,-9,-7,-14,-12)
> 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,]   -1   -1   -6  -20  -15   -3
 [2,]   -2    1   -3  -24  -15    1
 [3,]   -5   -1   -3  -24  -13   -2
 [4,]   -4    2   -7  -22   -8   -1
 [5,]   -6    2   -9  -19  -13    1
 [6,]   -2    1  -11  -18   -9   -3
 [7,]   -2   -1  -13  -17   -7   -4
 [8,]   -2   -2  -11  -11   -4   -9
 [9,]   -2   -2   -9  -11   -4   -9
[10,]    2   -1  -17  -12   -2   -7
[11,]    1   -8  -22  -10    0  -14
[12,]   -8   -4  -25  -15   -2  -12
> 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]  -2.583333  -1.166667 -11.333333 -16.916667  -7.666667  -5.166667
> arr.sd
[1] 2.810963 2.790677 6.958753 5.107184 5.365434 4.969605
> arr.range
[1] 10 10 22 14 15 15
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
     3.2277      -0.1926  

> (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