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(15.14,14.2,13.83,14.31,14.04,14.9,14.92,15.36,15.5,15.65,16.18,15.44,15.58,15.24,15.33,16.07,15.82,15.87,15.72,17.07,16.83,17.52,17.76,17.36,17.95,16.71,17.14,16.72,17.26,17.24,17.69,18.13,18.08,18.18,18.18,17.64,17.89,16.82,16.61,16.66,17.02,16.91,17.18,18.06,17.58,17.48,17.54,17.44,17.79,16.79,16.19,16.62,16.39,16.54,17.26,18,17.29,18.16,17.82,17.48,18.31,17.04,17.03,16.97,17.11,17.12,17.69,18.5,18.27,18.45,18.35,18.03,18.49,18.07,17.8,17.88,18.12,18.68,18.8,19.64,19.56,19.3,20.07,19.82,20.29,19.36,18.74,18.87,18.87,18.91,19.31,20.06,20.72,20.42,20.58,20.58,21.18,19.87,19.83,19.48,19.49,19.4,19.89,20.44,20.07,19.75,19.54,19.07,19.55,18.01,17.5,17.41,17.47,17.6,17.64,18.3,18.27,17.99,18.04,17.62,18.22,17.67,17.73,17.99,18.15,18.41,18.36,19.52,19.96,19.6,19.48,19.13)
> 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] 132
> (np <- floor(n / par1))
[1] 33
> 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]
[1,] 15.14 14.04 15.50 15.58 15.82 16.83 17.95 17.26 18.08 17.89 17.02 17.58
[2,] 14.20 14.90 15.65 15.24 15.87 17.52 16.71 17.24 18.18 16.82 16.91 17.48
[3,] 13.83 14.92 16.18 15.33 15.72 17.76 17.14 17.69 18.18 16.61 17.18 17.54
[4,] 14.31 15.36 15.44 16.07 17.07 17.36 16.72 18.13 17.64 16.66 18.06 17.44
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,] 17.79 16.39 17.29 18.31 17.11 18.27 18.49 18.12 19.56 20.29 18.87 20.72
[2,] 16.79 16.54 18.16 17.04 17.12 18.45 18.07 18.68 19.30 19.36 18.91 20.42
[3,] 16.19 17.26 17.82 17.03 17.69 18.35 17.80 18.80 20.07 18.74 19.31 20.58
[4,] 16.62 18.00 17.48 16.97 18.50 18.03 17.88 19.64 19.82 18.87 20.06 20.58
     [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33]
[1,] 21.18 19.49 20.07 19.55 17.47 18.27 18.22 18.15 19.96
[2,] 19.87 19.40 19.75 18.01 17.60 17.99 17.67 18.41 19.60
[3,] 19.83 19.89 19.54 17.50 17.64 18.04 17.73 18.36 19.48
[4,] 19.48 20.44 19.07 17.41 18.30 17.62 17.99 19.52 19.13
> 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] 14.3700 14.8050 15.6925 15.5550 16.1200 17.3675 17.1300 17.5800 18.0200
[10] 16.9950 17.2925 17.5100 16.8475 17.0475 17.6875 17.3375 17.6050 18.2750
[19] 18.0600 18.8100 19.6875 19.3150 19.2875 20.5750 20.0900 19.8050 19.6075
[28] 18.1175 17.7525 17.9800 17.9025 18.6100 19.5425
> arr.sd
 [1] 0.55287129 0.55241892 0.33678628 0.37224544 0.63639610 0.39423977
 [7] 0.58223707 0.42134705 0.25768197 0.60335175 0.52353765 0.06218253
[13] 0.67716935 0.73988175 0.38378596 0.64906985 0.65536250 0.17916473
[19] 0.30822070 0.62769419 0.33180064 0.70268533 0.55198883 0.12261049
[25] 0.74748467 0.47388466 0.41939440 0.99087083 0.37214469 0.26919633
[31] 0.25316332 0.61703593 0.34238137
> arr.range
 [1] 1.31 1.32 0.74 0.83 1.35 0.93 1.24 0.89 0.54 1.28 1.15 0.14 1.60 1.61 0.87
[16] 1.34 1.39 0.42 0.69 1.52 0.77 1.55 1.19 0.30 1.70 1.04 1.00 2.14 0.83 0.65
[31] 0.55 1.37 0.83
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    0.76470     -0.01619  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

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

Coefficients:
  (Intercept)  log(arr.mean)  
        2.090         -1.026  

> (lm2 <- lm(arr.range~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    1.67367     -0.03425  

> postscript(file="/var/wessaorg/rcomp/tmp/1gkh01322555757.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/20g5s1322555757.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/38lx61322555757.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/40v0k1322555757.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5pkz81322555757.tab") 
> 
> try(system("convert tmp/1gkh01322555757.ps tmp/1gkh01322555757.png",intern=TRUE))
character(0)
> try(system("convert tmp/20g5s1322555757.ps tmp/20g5s1322555757.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.665   0.136   0.799