R version 2.6.2 (2008-02-08)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.43,1.44,1.47,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.48,1.57,1.58,1.58,1.58,1.58,1.59,1.6,1.6,1.6,1.6,1.61,1.61,1.62,1.63,1.63,1.63,1.63,1.63,1.64,1.64,1.64,1.65,1.65)
> par1 = '12'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 62
> (np <- floor(n / par1))
[1] 5
> 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]
 [1,] 1.43 1.48 1.48 1.48 1.60
 [2,] 1.43 1.48 1.48 1.48 1.61
 [3,] 1.43 1.48 1.48 1.48 1.61
 [4,] 1.43 1.48 1.48 1.57 1.62
 [5,] 1.43 1.48 1.48 1.58 1.63
 [6,] 1.43 1.48 1.48 1.58 1.63
 [7,] 1.43 1.48 1.48 1.58 1.63
 [8,] 1.43 1.48 1.48 1.58 1.63
 [9,] 1.44 1.48 1.48 1.59 1.63
[10,] 1.47 1.48 1.48 1.60 1.64
[11,] 1.48 1.48 1.48 1.60 1.64
[12,] 1.48 1.48 1.48 1.60 1.64
> 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] 1.442500 1.480000 1.480000 1.560000 1.625833
> arr.sd
[1] 0.02094365 0.00000000 0.00000000 0.04917501 0.01311372
> arr.range
[1] 0.05 0.00 0.00 0.12 0.04
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.11634      0.08762  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 
  NA/NaN/Inf in foreign function call (arg 4)
Calls: lm -> lm.fit -> .Fortran
Execution halted