R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(2.4,2.4,2.5,2.6,2.4,2.6,2.4,2.3,2.4,2.4,2.4,2.4,2.4,2.4,2.4,2.4,2.5,2.1,2.1,2,2,2,1.9,1.9,2,1.8,1.6,1.3,1.4,1.4,1.5,1.7,1.6,1.5,1.6,1.5,1.1,1.1,1.1,1.4,1.3,1.4,1.3,1.1,1,0.9,0.8,0.8,0.8,0.8,1,1.1,1,0.9,1.1,1.2,1.2,1.4,1.5,1.7,1.9,1.9,1.9,1.7,1.7,2.1,2,2,2.5,2.4,2.5,2.5,2,1.9,2.2,2.7,3.1,2.8,2.6,2.3,2.2,2.2,2,2,2.6,2.5,2.5,2.3,2,1.9,2,2.1,2.1,2.3,2.3,2.3,2.1,2.4,2.5,2.1,1.8,1.9,1.9,2.1,2.2,2,2.2,2,1.9,1.6,1.7,2,2.5,2.4,2.3,2.3,2.1,2.4,2.2,2.4,1.9,2.1,2.1,2.1,2,2.1,2.2,2.2,2.6,2.5,2.3,2.2,2.4,2.3,2.2,2.5,2.5,2.5,2.4,2.3,1.7,1.6,1.9,1.9,1.8,1.8,1.9,1.9,1.9,1.9,1.8,1.7,2.1,2.6,3.1,3.1,3.2,3.3,3.6,3.3,3.7,4,4,3.8,3.6,3.2,2.1,1.6,1.1,1.2,0.6,0.6,0,-0.1,-0.6,-0.2,-0.3,-0.1,0.5,0.9)
> 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] 180
> (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,]  2.4  2.4  2.0  1.1  0.8  1.9  2.0  2.6  2.1   1.9   1.9   2.4   1.8
 [2,]  2.4  2.4  1.8  1.1  0.8  1.9  1.9  2.5  2.4   1.6   2.1   2.3   1.8
 [3,]  2.5  2.4  1.6  1.1  1.0  1.9  2.2  2.5  2.5   1.7   2.1   2.2   1.9
 [4,]  2.6  2.4  1.3  1.4  1.1  1.7  2.7  2.3  2.1   2.0   2.1   2.5   1.9
 [5,]  2.4  2.5  1.4  1.3  1.0  1.7  3.1  2.0  1.8   2.5   2.0   2.5   1.9
 [6,]  2.6  2.1  1.4  1.4  0.9  2.1  2.8  1.9  1.9   2.4   2.1   2.5   1.9
 [7,]  2.4  2.1  1.5  1.3  1.1  2.0  2.6  2.0  1.9   2.3   2.2   2.4   1.8
 [8,]  2.3  2.0  1.7  1.1  1.2  2.0  2.3  2.1  2.1   2.3   2.2   2.3   1.7
 [9,]  2.4  2.0  1.6  1.0  1.2  2.5  2.2  2.1  2.2   2.1   2.6   1.7   2.1
[10,]  2.4  2.0  1.5  0.9  1.4  2.4  2.2  2.3  2.0   2.4   2.5   1.6   2.6
[11,]  2.4  1.9  1.6  0.8  1.5  2.5  2.0  2.3  2.2   2.2   2.3   1.9   3.1
[12,]  2.4  1.9  1.5  0.8  1.7  2.5  2.0  2.3  2.0   2.4   2.2   1.9   3.1
      [,14] [,15]
 [1,]   3.2   1.1
 [2,]   3.3   1.2
 [3,]   3.6   0.6
 [4,]   3.3   0.6
 [5,]   3.7   0.0
 [6,]   4.0  -0.1
 [7,]   4.0  -0.6
 [8,]   3.8  -0.2
 [9,]   3.6  -0.3
[10,]   3.2  -0.1
[11,]   2.1   0.5
[12,]   1.6   0.9
> 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] 2.433333 2.175000 1.575000 1.108333 1.141667 2.091667 2.333333 2.241667
 [9] 2.100000 2.150000 2.191667 2.183333 2.133333 3.283333 0.300000
> arr.sd
 [1] 0.08876254 0.22613351 0.19128750 0.21087839 0.27784343 0.30587678
 [7] 0.37979261 0.22343733 0.20449494 0.29387691 0.19752253 0.32427074
[13] 0.50692179 0.73340220 0.59237580
> arr.range
 [1] 0.3 0.6 0.7 0.6 0.9 0.8 1.2 0.7 0.7 0.9 0.7 0.9 1.4 2.4 1.8
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    0.28235      0.01772  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.1601        -0.2012  

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

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

Coefficients:
(Intercept)     arr.mean  
    0.82005      0.07809  

> postscript(file="/var/wessaorg/rcomp/tmp/1i7361323208178.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/wessaorg/rcomp/tmp/2ou0e1323208178.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/3csjt1323208178.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/42vd01323208178.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/wessaorg/rcomp/tmp/5yhr41323208178.tab") 
> 
> try(system("convert tmp/1i7361323208178.ps tmp/1i7361323208178.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ou0e1323208178.ps tmp/2ou0e1323208178.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.609   0.102   0.712