R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(13.81,13.9,13.91,13.94,13.96,14.01,14.01,14.06,14.09,14.13,14.12,14.13,14.14,14.16,14.21,14.26,14.29,14.32,14.33,14.39,14.48,14.44,14.46,14.48,14.53,14.58,14.62,14.62,14.61,14.65,14.68,14.7,14.78,14.84,14.89,14.89,15.13,15.25,15.33,15.36,15.4,15.4,15.41,15.47,15.54,15.55,15.59,15.65,15.75,15.86,15.89,15.94,15.93,15.95,15.99,15.99,16.06,16.08,16.07,16.11,16.15,16.18,16.3,16.42,16.49,16.5,16.58,16.64,16.66,16.81,16.91,16.92,16.95,17.11,17.16,17.16,17.27,17.34,17.39,17.43,17.45,17.5,17.56,17.65)
> 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] 84
> (np <- floor(n / par1))
[1] 21
> 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,] 13.81 13.96 14.09 14.14 14.29 14.48 14.53 14.61 14.78 15.13 15.40 15.54
[2,] 13.90 14.01 14.13 14.16 14.32 14.44 14.58 14.65 14.84 15.25 15.40 15.55
[3,] 13.91 14.01 14.12 14.21 14.33 14.46 14.62 14.68 14.89 15.33 15.41 15.59
[4,] 13.94 14.06 14.13 14.26 14.39 14.48 14.62 14.70 14.89 15.36 15.47 15.65
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 15.75 15.93 16.06 16.15 16.49 16.66 16.95 17.27 17.45
[2,] 15.86 15.95 16.08 16.18 16.50 16.81 17.11 17.34 17.50
[3,] 15.89 15.99 16.07 16.30 16.58 16.91 17.16 17.39 17.56
[4,] 15.94 15.99 16.11 16.42 16.64 16.92 17.16 17.43 17.65
> 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] 13.8900 14.0100 14.1175 14.1925 14.3325 14.4650 14.5875 14.6600 14.8500
[10] 15.2675 15.4200 15.5825 15.8600 15.9650 16.0800 16.2625 16.5525 16.8250
[19] 17.0950 17.3575 17.5400
> arr.sd
 [1] 0.05597619 0.04082483 0.01892969 0.05377422 0.04193249 0.01914854
 [7] 0.04272002 0.03915780 0.05228129 0.10275375 0.03366502 0.04991660
[13] 0.08041559 0.03000000 0.02160247 0.12338963 0.07088723 0.12069245
[19] 0.09949874 0.06898067 0.08602325
> arr.range
 [1] 0.13 0.10 0.04 0.12 0.10 0.04 0.09 0.09 0.11 0.23 0.07 0.11 0.19 0.06 0.05
[16] 0.27 0.15 0.26 0.21 0.16 0.20
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.18921      0.01608  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -14.269          4.131  

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

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

Coefficients:
(Intercept)     arr.mean  
   -0.40511      0.03474  

> postscript(file="/var/www/html/rcomp/tmp/13tdy1291210801.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/www/html/rcomp/tmp/23tdy1291210801.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/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/www/html/rcomp/tmp/3hvpl1291210801.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4d5nc1291210801.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/www/html/rcomp/tmp/5dxjr1291210801.tab") 
> 
> try(system("convert tmp/13tdy1291210801.ps tmp/13tdy1291210801.png",intern=TRUE))
character(0)
> try(system("convert tmp/23tdy1291210801.ps tmp/23tdy1291210801.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.536   0.305   1.550