R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(15.14,15.09,15.17,15.18,15.21,15.27,15.28,15.3,15.34,15.33,15.27,15.35,15.38,15.38,15.39,15.4,15.39,15.43,15.43,15.47,15.48,15.47,15.58,15.56,15.61,15.56,15.62,15.63,15.58,15.65,15.79,15.76,15.77,15.79,15.87,15.79,15.9,15.96,16.05,16.18,16.29,16.43,16.38,16.39,16.35,16.48,16.52,16.44,16.46,16.52,16.47,16.59,16.59,16.59,16.54,16.48,16.47,16.56,16.61,16.57,16.72,16.69,16.72,16.81,16.75,16.85,16.84,16.92,17.02,17.11,17.2,17.3,17.37,17.42,17.51,17.56,17.62,17.59,17.78,17.73,17.79,17.85,17.86,17.79,17.97,17.96,18.03,18.02,18.03,18.14,18.16,18.24,18.28,18.18,18.19,18.32)
> 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]
[1,] 15.14 15.21 15.34 15.38 15.39 15.48 15.61 15.58 15.77 15.90 16.29 16.35
[2,] 15.09 15.27 15.33 15.38 15.43 15.47 15.56 15.65 15.79 15.96 16.43 16.48
[3,] 15.17 15.28 15.27 15.39 15.43 15.58 15.62 15.79 15.87 16.05 16.38 16.52
[4,] 15.18 15.30 15.35 15.40 15.47 15.56 15.63 15.76 15.79 16.18 16.39 16.44
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,] 16.46 16.59 16.47 16.72 16.75 17.02 17.37 17.62 17.79 17.97 18.03 18.28
[2,] 16.52 16.59 16.56 16.69 16.85 17.11 17.42 17.59 17.85 17.96 18.14 18.18
[3,] 16.47 16.54 16.61 16.72 16.84 17.20 17.51 17.78 17.86 18.03 18.16 18.19
[4,] 16.59 16.48 16.57 16.81 16.92 17.30 17.56 17.73 17.79 18.02 18.24 18.32
> 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] 15.1450 15.2650 15.3225 15.3875 15.4300 15.5225 15.6050 15.6950 15.8050
[10] 16.0225 16.3725 16.4475 16.5100 16.5500 16.5525 16.7350 16.8400 17.1575
[19] 17.4650 17.6800 17.8225 17.9950 18.1425 18.2425
> arr.sd
 [1] 0.040414519 0.038729833 0.035939764 0.009574271 0.032659863 0.055602758
 [7] 0.031091264 0.097467943 0.044347116 0.121757957 0.059090326 0.072743843
[13] 0.059441848 0.052281290 0.059090326 0.051961524 0.069761498 0.120104121
[19] 0.085829288 0.089814624 0.037749172 0.035118846 0.086554414 0.068495742
> arr.range
 [1] 0.09 0.09 0.08 0.02 0.08 0.11 0.07 0.21 0.10 0.28 0.14 0.17 0.13 0.11 0.14
[16] 0.12 0.17 0.28 0.19 0.19 0.07 0.07 0.21 0.14
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.11201      0.01047  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -13.689          3.843  

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

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

Coefficients:
(Intercept)     arr.mean  
   -0.23305      0.02237  

> postscript(file="/var/www/html/rcomp/tmp/1qnmg1218478697.ps",horizontal=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/2b7zh1218478697.ps",horizontal=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/3u4sy1218478697.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4zfun1218478697.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5kl2a1218478697.tab") 
> 
> system("convert tmp/1qnmg1218478697.ps tmp/1qnmg1218478697.png")
> system("convert tmp/2b7zh1218478697.ps tmp/2b7zh1218478697.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.379   0.462   1.474