R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(12.32,12.34,12.36,12.54,12.77,12.79,12.96,12.96,13,13.19,13.25,13.61,13.8,13.83,14.04,14.16,14.2,14.27,14.31,14.69,14.9,14.92,15.01,15.09,15.14,15.24,15.33,15.36,15.44,15.5,15.58,15.65,15.72,15.82,15.87,16.07,16.18,16.19,16.39,16.54,16.61,16.62,16.66,16.71,16.72,16.79,16.82,16.83,16.91,16.97,17.02,17.03,17.04,17.07,17.11,17.12,17.14,17.18,17.24,17.26,17.26,17.29,17.36,17.44,17.48,17.48,17.52,17.54,17.58,17.64,17.69,17.69,17.76,17.79,17.82,17.89,17.95,18,18.03,18.06,18.08,18.13,18.16,18.18,18.18,18.27,18.31,18.35,18.45,18.5)
> 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] 90
> (np <- floor(n / par1))
[1] 22
> 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,] 12.32 12.77 13.00 13.80 14.20 14.90 15.14 15.44 15.72 16.18 16.61 16.72
[2,] 12.34 12.79 13.19 13.83 14.27 14.92 15.24 15.50 15.82 16.19 16.62 16.79
[3,] 12.36 12.96 13.25 14.04 14.31 15.01 15.33 15.58 15.87 16.39 16.66 16.82
[4,] 12.54 12.96 13.61 14.16 14.69 15.09 15.36 15.65 16.07 16.54 16.71 16.83
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
[1,] 16.91 17.04 17.14 17.26 17.48 17.58 17.76 17.95 18.08 18.18
[2,] 16.97 17.07 17.18 17.29 17.48 17.64 17.79 18.00 18.13 18.27
[3,] 17.02 17.11 17.24 17.36 17.52 17.69 17.82 18.03 18.16 18.31
[4,] 17.03 17.12 17.26 17.44 17.54 17.69 17.89 18.06 18.18 18.35
> 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] 12.3900 12.8700 13.2625 13.9575 14.3675 14.9800 15.2675 15.5425 15.8700
[10] 16.3250 16.6500 16.7900 16.9825 17.0850 17.2050 17.3375 17.5050 17.6500
[19] 17.8150 18.0100 18.1375 18.2775
> arr.sd
 [1] 0.10132456 0.10424331 0.25500000 0.17211914 0.21975365 0.08755950
 [7] 0.09912114 0.09178780 0.14719601 0.17291616 0.04546061 0.04966555
[13] 0.05500000 0.03696846 0.05507571 0.08015610 0.03000000 0.05228129
[19] 0.05567764 0.04690416 0.04349329 0.07274384
> arr.range
 [1] 0.22 0.19 0.61 0.36 0.49 0.19 0.22 0.21 0.35 0.36 0.10 0.11 0.12 0.08 0.12
[16] 0.18 0.06 0.11 0.13 0.11 0.10 0.17
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    0.46738     -0.02317  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
        7.388         -3.580  

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

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

Coefficients:
(Intercept)     arr.mean  
    1.01619     -0.05015  

> postscript(file="/var/yougetitorg/rcomp/tmp/1n9by1305063734.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/yougetitorg/rcomp/tmp/2qsig1305063734.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/yougetitorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/yougetitorg/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/yougetitorg/rcomp/tmp/3tk5i1305063734.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/yougetitorg/rcomp/tmp/4oy4u1305063734.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/yougetitorg/rcomp/tmp/5v1oc1305063734.tab") 
> 
> try(system("convert tmp/1n9by1305063734.ps tmp/1n9by1305063734.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qsig1305063734.ps tmp/2qsig1305063734.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.610   0.370   0.828