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(217.8,218.79,218.99,219.53,219.55,219.74,219.74,219.74,219.8,219.97,220.07,220.07,220.1,225.8,233.17,233.83,233.63,233.63,233.65,233.8,233.84,233.74,233.88,233.88,233.81,234.68,236.14,236.91,236.87,236.78,236.78,236.9,236.94,236.97,236.96,236.94,236.99,237.24,237.62,237.54,237.41,237.4,237.41,237.28,237.17,237.18,237.18,237.18,236.77,239.23,240.23,240.33,240.33,240.34,240.34,240.27,240.29,240.29,240.29,240.29,240.31,239.95,242.33,242.11,241.53,241.53,241.53,241.41,241.41,241.66,241.8,241.99)
> par1 = '4'
> #'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] 18
> 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]   [,8]   [,9]  [,10]
[1,] 217.80 219.55 219.80 220.10 233.63 233.84 233.81 236.87 236.94 236.99
[2,] 218.79 219.74 219.97 225.80 233.63 233.74 234.68 236.78 236.97 237.24
[3,] 218.99 219.74 220.07 233.17 233.65 233.88 236.14 236.78 236.96 237.62
[4,] 219.53 219.74 220.07 233.83 233.80 233.88 236.91 236.90 236.94 237.54
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]
[1,] 237.41 237.17 236.77 240.33 240.29 240.31 241.53 241.41
[2,] 237.40 237.18 239.23 240.34 240.29 239.95 241.53 241.66
[3,] 237.41 237.18 240.23 240.34 240.29 242.33 241.53 241.80
[4,] 237.28 237.18 240.33 240.27 240.29 242.11 241.41 241.99
> 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] 218.7775 219.6925 219.9775 228.2250 233.6775 233.8350 235.3850 236.8325
 [9] 236.9525 237.3475 237.3750 237.1775 239.1400 240.3200 240.2900 241.1750
[17] 241.5000 241.7150
> arr.sd
 [1] 0.72274362 0.09500000 0.12737739 6.52598141 0.08220908 0.06608076
 [7] 1.39920215 0.06184658 0.01500000 0.28906458 0.06350853 0.00500000
[13] 1.65622060 0.03366502 0.00000000 1.21889294 0.06000000 0.24419937
> arr.range
 [1]  1.73  0.19  0.27 13.73  0.17  0.14  3.10  0.12  0.03  0.63  0.13  0.01
[13]  3.56  0.07  0.00  2.38  0.12  0.58
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    8.75009     -0.03433  

> (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