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(0.5800,0.5800,0.5900,0.6000,0.6000,0.6100,0.6200,0.6100,0.6200,0.6200,0.6200,0.6300,0.6300,0.6300,0.6300,0.6300,0.6300,0.6300,0.6300,0.6400,0.6300,0.6300,0.6300,0.6300,0.6300,0.6400,0.6500,0.6500,0.6500,0.6500,0.6500,0.6600,0.6500,0.6600,0.6600,0.6600,0.6600,0.6800,0.6900,0.7000,0.7100,0.7100,0.7000,0.7000,0.7000,0.7000,0.7100,0.7000,0.7000,0.7000,0.6900,0.7000,0.6900,0.6900,0.6900,0.7000,0.7000,0.7100,0.7100,0.7100,0.7200,0.7300,0.7400,0.7400,0.7400,0.7400,0.7500,0.7500,0.7600,0.7600,0.7600,0.7600,0.7600,0.7700,0.7700,0.7800,0.7800,0.7800,0.7800,0.7800,0.7800,0.7800,0.8000,0.8000,0.8000,0.8100,0.8100,0.8100,0.8000,0.8100,0.8100,0.8100,0.8000,0.8200,0.8300,0.8300)
> 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] 96
> (np <- floor(n / par1))
[1] 24
> 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,] 0.58 0.60 0.62 0.63 0.63 0.63 0.63 0.65 0.65  0.66  0.71  0.70  0.70  0.69
[2,] 0.58 0.61 0.62 0.63 0.63 0.63 0.64 0.65 0.66  0.68  0.71  0.70  0.70  0.69
[3,] 0.59 0.62 0.62 0.63 0.63 0.63 0.65 0.65 0.66  0.69  0.70  0.71  0.69  0.69
[4,] 0.60 0.61 0.63 0.63 0.64 0.63 0.65 0.66 0.66  0.70  0.70  0.70  0.70  0.70
     [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,]  0.70  0.72  0.74  0.76  0.76  0.78  0.78  0.80  0.80  0.80
[2,]  0.71  0.73  0.74  0.76  0.77  0.78  0.78  0.81  0.81  0.82
[3,]  0.71  0.74  0.75  0.76  0.77  0.78  0.80  0.81  0.81  0.83
[4,]  0.71  0.74  0.75  0.76  0.78  0.78  0.80  0.81  0.81  0.83
> 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] 0.5875 0.6100 0.6225 0.6300 0.6325 0.6300 0.6425 0.6525 0.6575 0.6825
[11] 0.7050 0.7025 0.6975 0.6925 0.7075 0.7325 0.7450 0.7600 0.7700 0.7800
[21] 0.7900 0.8075 0.8075 0.8200
> arr.sd
 [1] 0.009574271 0.008164966 0.005000000 0.000000000 0.005000000 0.000000000
 [7] 0.009574271 0.005000000 0.005000000 0.017078251 0.005773503 0.005000000
[13] 0.005000000 0.005000000 0.005000000 0.009574271 0.005773503 0.000000000
[19] 0.008164966 0.000000000 0.011547005 0.005000000 0.005000000 0.014142136
> arr.range
 [1] 0.02 0.02 0.01 0.00 0.01 0.00 0.02 0.01 0.01 0.04 0.01 0.01 0.01 0.01 0.01
[16] 0.02 0.01 0.00 0.02 0.00 0.02 0.01 0.01 0.03
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   0.001584     0.006602  

> (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