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(9.26,9.27,9.29,9.27,9.29,9.31,9.33,9.35,9.34,9.35,9.38,9.43,9.47,9.5,9.55,9.58,9.61,9.57,9.61,9.65,9.62,9.63,9.62,9.63,9.65,9.72,9.75,9.77,9.78,9.82,9.84,9.9,9.94,9.96,10.03,10.03,10.12,10.12,10.05,10.14,10.17,10.2,10.2,10.35,10.43,10.52,10.57,10.57,10.57,10.65,10.57,10.61,10.63,10.71,10.72,10.77,10.79,10.82,10.9,10.83,10.92,10.91,10.88,10.87,11,10.99,11.03,11.04,10.99,10.9,11,10.99,10.92,10.98,11.15,11.19,11.33,11.38,11.4,11.45,11.56,11.61,11.82,11.77,11.85,11.82,11.92,11.86,11.87,11.94,11.86,11.92,11.83,11.91,11.93,11.99,11.96,12.12,11.85,12.01,12.1,12.21,12.31,12.31,12.39,12.35,12.41,12.51,12.27,12.51,12.44,12.47,12.51,12.58,12.5,12.52,12.59,12.51,12.67,12.64,12.54,12.6,12.67,12.62,12.72,12.85,12.85,12.82,12.79,12.94,12.71,12.56)
> 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] [,13]
[1,] 9.26 9.29 9.34 9.47 9.61 9.62 9.65 9.78  9.94 10.12 10.17 10.43 10.57
[2,] 9.27 9.31 9.35 9.50 9.57 9.63 9.72 9.82  9.96 10.12 10.20 10.52 10.65
[3,] 9.29 9.33 9.38 9.55 9.61 9.62 9.75 9.84 10.03 10.05 10.20 10.57 10.57
[4,] 9.27 9.35 9.43 9.58 9.65 9.63 9.77 9.90 10.03 10.14 10.35 10.57 10.61
     [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,] 10.63 10.79 10.92 11.00 10.99 10.92 11.33 11.56 11.85 11.87 11.83 11.96
[2,] 10.71 10.82 10.91 10.99 10.90 10.98 11.38 11.61 11.82 11.94 11.91 12.12
[3,] 10.72 10.90 10.88 11.03 11.00 11.15 11.40 11.82 11.92 11.86 11.93 11.85
[4,] 10.77 10.83 10.87 11.04 10.99 11.19 11.45 11.77 11.86 11.92 11.99 12.01
     [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33]
[1,] 12.10 12.39 12.27 12.51 12.59 12.54 12.72 12.79
[2,] 12.21 12.35 12.51 12.58 12.51 12.60 12.85 12.94
[3,] 12.31 12.41 12.44 12.50 12.67 12.67 12.85 12.71
[4,] 12.31 12.51 12.47 12.52 12.64 12.62 12.82 12.56
> 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]  9.2725  9.3200  9.3750  9.5250  9.6100  9.6250  9.7225  9.8350  9.9900
[10] 10.1075 10.2300 10.5225 10.6000 10.7075 10.8350 10.8950 11.0150 10.9700
[19] 11.0600 11.3900 11.6900 11.8625 11.8975 11.9150 11.9850 12.2325 12.4150
[28] 12.4225 12.5275 12.6025 12.6075 12.8100 12.7500
> arr.sd
 [1] 0.012583057 0.025819889 0.040414519 0.049328829 0.032659863 0.005773503
 [7] 0.052519838 0.050000000 0.046904158 0.039475731 0.081240384 0.066017674
[13] 0.038297084 0.057951129 0.046547467 0.023804761 0.023804761 0.046904158
[19] 0.130384048 0.049665548 0.124632794 0.041932485 0.038622101 0.066080759
[25] 0.112101145 0.100124922 0.068068593 0.105633013 0.035939764 0.069940451
[31] 0.053774219 0.061644140 0.158534959
> arr.range
 [1] 0.03 0.06 0.09 0.11 0.08 0.01 0.12 0.12 0.09 0.09 0.18 0.14 0.08 0.14 0.11
[16] 0.05 0.05 0.10 0.27 0.12 0.26 0.10 0.08 0.16 0.27 0.21 0.16 0.24 0.08 0.16
[31] 0.13 0.13 0.38
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.11424      0.01572  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -11.241          3.437  

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

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

Coefficients:
(Intercept)     arr.mean  
   -0.27027      0.03656  

> postscript(file="/var/wessaorg/rcomp/tmp/10k5m1322588032.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/2ekem1322588032.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/3ta2u1322588032.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4r9441322588032.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5li841322588032.tab") 
> 
> try(system("convert tmp/10k5m1322588032.ps tmp/10k5m1322588032.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ekem1322588032.ps tmp/2ekem1322588032.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.756   0.128   0.884