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(1.08,1.08,1.09,1.1,1.1,1.11,1.1,1.1,1.11,1.11,1.11,1.11,1.11,1.12,1.11,1.11,1.12,1.12,1.11,1.12,1.11,1.11,1.1,1.1,1.1,1.11,1.1,1.1,1.09,1.1,1.1,1.11,1.13,1.13,1.13,1.13,1.14,1.14,1.14,1.15,1.15,1.15,1.15,1.15,1.15,1.14,1.14,1.14,1.13,1.12,1.13,1.13,1.13,1.12,1.13,1.12,1.12,1.11,1.11,1.11,1.11,1.14,1.15,1.15,1.16,1.15,1.16,1.13,1.13,1.12,1.12,1.11,1.11)
> 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] 73
> (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] [,11] [,12] [,13] [,14]
[1,] 1.08 1.10 1.11 1.11 1.12 1.11 1.10 1.09 1.13  1.14  1.15  1.15  1.13  1.13
[2,] 1.08 1.11 1.11 1.12 1.12 1.11 1.11 1.10 1.13  1.14  1.15  1.14  1.12  1.12
[3,] 1.09 1.10 1.11 1.11 1.11 1.10 1.10 1.10 1.13  1.14  1.15  1.14  1.13  1.13
[4,] 1.10 1.10 1.11 1.11 1.12 1.10 1.10 1.11 1.13  1.15  1.15  1.14  1.13  1.12
     [,15] [,16] [,17] [,18]
[1,]  1.12  1.11  1.16  1.13
[2,]  1.11  1.14  1.15  1.12
[3,]  1.11  1.15  1.16  1.12
[4,]  1.11  1.15  1.13  1.11
> 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] 1.0875 1.1025 1.1100 1.1125 1.1175 1.1050 1.1025 1.1000 1.1300 1.1425
[11] 1.1500 1.1425 1.1275 1.1250 1.1125 1.1375 1.1500 1.1200
> arr.sd
 [1] 0.009574271 0.005000000 0.000000000 0.005000000 0.005000000 0.005773503
 [7] 0.005000000 0.008164966 0.000000000 0.005000000 0.000000000 0.005000000
[13] 0.005000000 0.005773503 0.005000000 0.018929694 0.014142136 0.008164966
> arr.range
 [1] 0.02 0.01 0.00 0.01 0.01 0.01 0.01 0.02 0.00 0.01 0.00 0.01 0.01 0.01 0.01
[16] 0.04 0.03 0.02
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.01922      0.02263  

> (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