R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(0.24,0.23,0.23,0.24,0.23,0.23,0.25,0.21,0.26,0.25,0.24,0.24,0.27,0.25,0.26,0.29,0.24,0.26,0.24,0.26,0.25,0.26,0.24,0.21,0.20,0.22,0.20,0.21,0.20,0.19,0.20,0.20,0.21,0.24,0.22,0.19,0.23,0.23,0.23,0.22,0.23,0.25,0.25,0.22,0.25,0.25,0.24,0.19,0.24,0.26,0.24,0.24,0.25,0.23,0.27,0.24,0.26,0.27,0.29,0.28,0.32,0.29,0.27,0.26,0.28,0.31,0.29,0.31,0.31,0.32,0.32,0.26,0.31,0.31,0.31,0.31,0.29,0.27,0.30,0.27,0.27,0.30,0.28,0.24,0.28,0.28,0.33,0.28,0.29,0.25,0.31,0.29,0.37,0.31,0.29,0.28,0.30,0.32,0.31,0.28,0.29,0.29,0.28,0.26,0.28,0.30,0.33,0.31,0.37,0.36,0.37,0.37,0.36,0.33,0.33,0.40,0.32,0.39,0.39,0.37,0.37,0.30,0.33,0.33,0.34,0.35,0.34,0.37,0.37,0.37,0.36,0.32,0.33,0.35,0.36,0.35,0.37,0.35,0.32,0.33,0.28,0.32,0.35,0.30,0.32,0.32,0.32,0.32,0.36,0.31,0.26,0.33,0.31,0.34,0.33,0.38,0.32,0.30,0.32,0.33,0.34,0.29,0.33,0.36,0.32,0.32,0.32,0.31,0.30,0.34,0.34,0.30,0.28,0.25,0.27,0.33,0.28,0.33,0.32,0.27,0.27,0.28,0.27,0.27,0.25,0.25,0.22,0.27)
> par1 = '12'
> #'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] 188
> (np <- floor(n / par1))
[1] 15
> 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,] 0.24 0.27 0.20 0.23 0.24 0.32 0.31 0.28 0.30  0.37  0.37  0.33  0.32
 [2,] 0.23 0.25 0.22 0.23 0.26 0.29 0.31 0.28 0.32  0.36  0.30  0.35  0.32
 [3,] 0.23 0.26 0.20 0.23 0.24 0.27 0.31 0.33 0.31  0.37  0.33  0.36  0.32
 [4,] 0.24 0.29 0.21 0.22 0.24 0.26 0.31 0.28 0.28  0.37  0.33  0.35  0.32
 [5,] 0.23 0.24 0.20 0.23 0.25 0.28 0.29 0.29 0.29  0.36  0.34  0.37  0.36
 [6,] 0.23 0.26 0.19 0.25 0.23 0.31 0.27 0.25 0.29  0.33  0.35  0.35  0.31
 [7,] 0.25 0.24 0.20 0.25 0.27 0.29 0.30 0.31 0.28  0.33  0.34  0.32  0.26
 [8,] 0.21 0.26 0.20 0.22 0.24 0.31 0.27 0.29 0.26  0.40  0.37  0.33  0.33
 [9,] 0.26 0.25 0.21 0.25 0.26 0.31 0.27 0.37 0.28  0.32  0.37  0.28  0.31
[10,] 0.25 0.26 0.24 0.25 0.27 0.32 0.30 0.31 0.30  0.39  0.37  0.32  0.34
[11,] 0.24 0.24 0.22 0.24 0.29 0.32 0.28 0.29 0.33  0.39  0.36  0.35  0.33
[12,] 0.24 0.21 0.19 0.19 0.28 0.26 0.24 0.28 0.31  0.37  0.32  0.30  0.38
      [,14] [,15]
 [1,]  0.32  0.30
 [2,]  0.30  0.34
 [3,]  0.32  0.34
 [4,]  0.33  0.30
 [5,]  0.34  0.28
 [6,]  0.29  0.25
 [7,]  0.33  0.27
 [8,]  0.36  0.33
 [9,]  0.32  0.28
[10,]  0.32  0.33
[11,]  0.32  0.32
[12,]  0.31  0.27
> 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] 0.2375000 0.2525000 0.2066667 0.2325000 0.2558333 0.2950000 0.2883333
 [8] 0.2966667 0.2958333 0.3633333 0.3458333 0.3341667 0.3250000 0.3216667
[15] 0.3008333
> arr.sd
 [1] 0.01288057 0.01959824 0.01435481 0.01764550 0.01880925 0.02315953
 [7] 0.02249579 0.03055050 0.01975225 0.02534609 0.02314316 0.02609714
[13] 0.02907670 0.01800673 0.03088346
> arr.range
 [1] 0.05 0.08 0.05 0.06 0.06 0.06 0.07 0.12 0.07 0.08 0.07 0.09 0.12 0.07 0.09
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  -0.001531     0.081525  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -2.382          1.169  

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

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

Coefficients:
(Intercept)     arr.mean  
   0.003517     0.249846  

> postscript(file="/var/www/html/rcomp/tmp/1kfd11228738068.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/2a6ra1228738068.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/34umm1228738068.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4kb441228738068.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5bni01228738068.tab") 
> 
> system("convert tmp/1kfd11228738068.ps tmp/1kfd11228738068.png")
> system("convert tmp/2a6ra1228738068.ps tmp/2a6ra1228738068.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.524   0.299   0.630