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(57.7,63.6,78,77.4,74.1,85.9,82,78.4,68.1,70.9,85.2,149.6,57.9,63.7,85,66.1,80.2,83.4,85.7,81.8,69.4,76.4,90.3,157.3,65.3,68.4,72.7,86.6,82.6,84.8,93.4,82.2,75.2,83.9,85.4,166.3,70.4,73.9,82.4,92.3,82.7,95.8,105.8,84.2,82.7,88.4,90.2,176.6,69.5,77.3,98.6,86.4,90.8,101.5,112.2,93.6,93.8,90.8,98.1,187.6,75,83.7,99.7,104.9,98.9,117.3,115.7,102.2,101.9,96.6,110,203.7,82.3,93.3,121.9,100.9,107.7,130,123.2,116.1,105.3,107.7,123.9,205.2,90.3,106.9,122.4,111.3,122.6,124.8,139.5,118.8,111,121.2,120.6,219.1,101.3,105,113.4,133.6,123.9,136.2,151.7,121.9,120.2,132.2,125.2,233.8)
> 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] 108
> (np <- floor(n / par1))
[1] 27
> 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,] 57.7 74.1  68.1 57.9 80.2  69.4 65.3 82.6  75.2  70.4  82.7  82.7  69.5
[2,] 63.6 85.9  70.9 63.7 83.4  76.4 68.4 84.8  83.9  73.9  95.8  88.4  77.3
[3,] 78.0 82.0  85.2 85.0 85.7  90.3 72.7 93.4  85.4  82.4 105.8  90.2  98.6
[4,] 77.4 78.4 149.6 66.1 81.8 157.3 86.6 82.2 166.3  92.3  84.2 176.6  86.4
     [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
[1,]  90.8  93.8  75.0  98.9 101.9  82.3 107.7 105.3  90.3 122.6 111.0 101.3
[2,] 101.5  90.8  83.7 117.3  96.6  93.3 130.0 107.7 106.9 124.8 121.2 105.0
[3,] 112.2  98.1  99.7 115.7 110.0 121.9 123.2 123.9 122.4 139.5 120.6 113.4
[4,]  93.6 187.6 104.9 102.2 203.7 100.9 116.1 205.2 111.3 118.8 219.1 133.6
     [,26] [,27]
[1,] 123.9 120.2
[2,] 136.2 132.2
[3,] 151.7 125.2
[4,] 121.9 233.8
> 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]  69.175  80.100  93.450  68.175  82.775  98.350  73.250  85.750 102.700
[10]  79.750  92.125 109.475  82.950  99.525 117.575  90.825 108.525 128.050
[19]  99.600 119.250 135.525 107.725 126.425 142.975 113.325 133.425 152.850
> arr.sd
 [1] 10.137184  5.037857 38.175079 11.732966  2.347161 40.248437  9.403014
 [8]  5.226535 42.637777  9.766780 10.834320 44.864045 12.511994  9.587970
[15] 46.779367 13.881252  9.329657 50.733454 16.712869  9.565389 47.178835
[22] 13.322256  9.062147 50.964718 14.433612 13.726222 54.190620
> arr.range
 [1]  20.3  11.8  81.5  27.1   5.5  87.9  21.3  11.2  91.1  21.9  23.1  93.9
[13]  29.1  21.4  96.8  29.9  18.4 107.1  39.6  22.3  99.9  32.1  20.7 108.1
[25]  32.3  29.8 113.6
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -27.2624       0.4791  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -7.535          2.235  

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

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

Coefficients:
(Intercept)     arr.mean  
   -55.1469       0.9975  

> postscript(file="/var/www/html/rcomp/tmp/13bsw1291465893.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/23bsw1291465893.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/3pb821291465893.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4su7p1291465893.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5wvow1291465893.tab") 
> 
> try(system("convert tmp/13bsw1291465893.ps tmp/13bsw1291465893.png",intern=TRUE))
character(0)
> try(system("convert tmp/23bsw1291465893.ps tmp/23bsw1291465893.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.528   0.313   1.233