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(192.89,194.76,194.76,194.76,194.76,194.76,194.76,194.76,194.76,194.76,194.76,194.76,194.76,194.76,199.15,199.15,199.15,199.15,199.15,199.15,199.15,199.15,199.15,199.15,199.15,200.4,200.4,200.4,200.4,200.4,200.4,200.4,200.4,200.4,200.4,200.4,200.4,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,204.15,212.25,212.25,212.25,212.25,212.25,212.25,212.25,212.25,212.25,212.25,212.25)
> 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] 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,] 192.89 194.76 199.15 200.40 204.15 204.15
 [2,] 194.76 194.76 200.40 204.15 204.15 212.25
 [3,] 194.76 199.15 200.40 204.15 204.15 212.25
 [4,] 194.76 199.15 200.40 204.15 204.15 212.25
 [5,] 194.76 199.15 200.40 204.15 204.15 212.25
 [6,] 194.76 199.15 200.40 204.15 204.15 212.25
 [7,] 194.76 199.15 200.40 204.15 204.15 212.25
 [8,] 194.76 199.15 200.40 204.15 204.15 212.25
 [9,] 194.76 199.15 200.40 204.15 204.15 212.25
[10,] 194.76 199.15 200.40 204.15 204.15 212.25
[11,] 194.76 199.15 200.40 204.15 204.15 212.25
[12,] 194.76 199.15 200.40 204.15 204.15 212.25
> 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] 194.6042 198.4183 200.2958 203.8375 204.1500 211.5750
> arr.sd
[1] 0.5398225 1.7088052 0.3608439 1.0825318 0.0000000 2.3382686
> arr.range
[1] 1.87 4.39 1.25 3.75 0.00 8.10
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -14.1756       0.0751  

> (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