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(102.5,77.7,82.8,77.3,103.1,99.7,99.5,107.2,96.7,97.1,105.2,151.2,102.7,75.4,87.2,83.7,105.8,111.5,99.7,111.2,101.5,110.9,116.3,164.9,118.1,83.7,84,107.2,113.7,120.7,111.2,112.4,112.5,130.4,130.7,174.3,132.2,91.8,104.2,104.8,131.4,141.2,132.7,135.7,136.9,151.2,144,201.5,149.6,108.7,122.8,126.7,139.9,162.5,142.7,151.6,148.1,159,157.8,226.7,153.7,122.3,117.6,166,154.5,183.9,164.4,173.3,160.2,166.4,170.3,238.4,166.8,122.5,141.8,140.5,173.8,188.8,168,187.4,177.7,183.8,196.1,264.6,193.7,141.3,170.1,163.7,190.1,230.7,195.9,210.3,204.7,210.3,221.2,288.2,203.2,162.4,149.2,195.3,213.7,227.9,212.1,226.8,212.6,220.9,228.1,311.6)
> 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] 108
> (np <- floor(n / par1))
[1] 9
> 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]
 [1,] 102.5 102.7 118.1 132.2 149.6 153.7 166.8 193.7 203.2
 [2,]  77.7  75.4  83.7  91.8 108.7 122.3 122.5 141.3 162.4
 [3,]  82.8  87.2  84.0 104.2 122.8 117.6 141.8 170.1 149.2
 [4,]  77.3  83.7 107.2 104.8 126.7 166.0 140.5 163.7 195.3
 [5,] 103.1 105.8 113.7 131.4 139.9 154.5 173.8 190.1 213.7
 [6,]  99.7 111.5 120.7 141.2 162.5 183.9 188.8 230.7 227.9
 [7,]  99.5  99.7 111.2 132.7 142.7 164.4 168.0 195.9 212.1
 [8,] 107.2 111.2 112.4 135.7 151.6 173.3 187.4 210.3 226.8
 [9,]  96.7 101.5 112.5 136.9 148.1 160.2 177.7 204.7 212.6
[10,]  97.1 110.9 130.4 151.2 159.0 166.4 183.8 210.3 220.9
[11,] 105.2 116.3 130.7 144.0 157.8 170.3 196.1 221.2 228.1
[12,] 151.2 164.9 174.3 201.5 226.7 238.4 264.6 288.2 311.6
> 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] 100.0000 105.9000 116.5750 133.9667 149.6750 164.2500 175.9833 201.6833
[9] 213.6500
> arr.sd
[1] 19.17441 22.39001 23.43878 27.87705 29.12319 30.40537 35.74800 37.15243
[9] 39.84213
> arr.range
[1]  73.9  89.5  90.6 109.7 118.0 120.8 142.1 146.9 162.4
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
     3.6363       0.1707  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.0830         0.8903  

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

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

Coefficients:
(Intercept)     arr.mean  
     9.7942       0.7092  

> postscript(file="/var/www/html/rcomp/tmp/1d6y81261307626.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/2axl11261307626.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/3hls01261307626.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4wx1q1261307626.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/53w451261307626.tab") 
> 
> try(system("convert tmp/1d6y81261307626.ps tmp/1d6y81261307626.png",intern=TRUE))
character(0)
> try(system("convert tmp/2axl11261307626.ps tmp/2axl11261307626.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.506   0.276   0.644