R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(-4,-5,-6,-6,-7,-12,-16,-18,-19,-20,-24,-17,-23,-25,-24,-17,-14,-16,-13,-10,-10,-12,-12,-20,-16,-12,-14,-7,-9,-9,-4,-3,1,-1,-2,1,-3,-2,0,-2,-4,-4,-7,-9,-13,-8,-13,-15,-15,-15,-10,-12,-11,-11,-17,-18,-19,-22,-24,-24,-20,-25,-22,-17,-9,-11,-13,-11,-9,-7,-3,-3,-6,-4,-8,-1,-2,-2,-1,1,2,2,-1,1,-1,-8,1,2,-2,-2,-2,-2,-6,-4,-5)
> 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] 95
> (np <- floor(n / par1))
[1] 7
> 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]
 [1,]   -4  -23  -16   -3  -15  -20   -6
 [2,]   -5  -25  -12   -2  -15  -25   -4
 [3,]   -6  -24  -14    0  -10  -22   -8
 [4,]   -6  -17   -7   -2  -12  -17   -1
 [5,]   -7  -14   -9   -4  -11   -9   -2
 [6,]  -12  -16   -9   -4  -11  -11   -2
 [7,]  -16  -13   -4   -7  -17  -13   -1
 [8,]  -18  -10   -3   -9  -18  -11    1
 [9,]  -19  -10    1  -13  -19   -9    2
[10,]  -20  -12   -1   -8  -22   -7    2
[11,]  -24  -12   -2  -13  -24   -3   -1
[12,]  -17  -20    1  -15  -24   -3    1
> 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] -12.833333 -16.333333  -6.250000  -6.666667 -16.500000 -12.500000  -1.583333
> arr.sd
[1] 6.978321 5.449493 5.801646 4.978743 5.036232 7.154147 3.117643
> arr.range
[1] 20 15 17 15 14 22 10
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
     4.1133      -0.1338  

> (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