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(2.46,2.46,2.45,2.45,2.46,2.43,2.44,2.44,2.43,2.43,2.42,2.43,2.43,2.42,2.41,2.42,2.39,2.4,2.39,2.4,2.41,2.41,2.41,2.41,2.42,2.43,2.43,2.43,2.44,2.42,2.44,2.42,2.42,2.42,2.43,2.44,2.43,2.44,2.44,2.45,2.45,2.43,2.44,2.45,2.46,2.44,2.43,2.42,2.41,2.43,2.41,2.43,2.43,2.44,2.43,2.44,2.43,2.44,2.44,2.43,2.43,2.43,2.43,2.44,2.47,2.48,2.49,2.5,2.51,2.49,2.49,2.48,2.48,2.48,2.5,2.5,2.5,2.5,2.5,2.48,2.49,2.48,2.5,2.5,2.49,2.48,2.47,2.46,2.43,2.42,2.43,2.45,2.45,2.46,2.44,2.45,2.45,2.42,2.41,2.39,2.39,2.38,2.37,2.37,2.38,2.39,2.41,2.42,2.48,2.53,2.56,2.56,2.53,2.57,2.56,2.57,2.58,2.57,2.6,2.63,2.72,2.83,2.9,2.92,2.94,2.95,2.98,3.02,3.16,3.2,3.18,3.17)
> 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] 132
> (np <- floor(n / par1))
[1] 11
> 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]
 [1,] 2.46 2.43 2.42 2.43 2.41 2.43 2.48 2.49 2.45  2.48  2.72
 [2,] 2.46 2.42 2.43 2.44 2.43 2.43 2.48 2.48 2.42  2.53  2.83
 [3,] 2.45 2.41 2.43 2.44 2.41 2.43 2.50 2.47 2.41  2.56  2.90
 [4,] 2.45 2.42 2.43 2.45 2.43 2.44 2.50 2.46 2.39  2.56  2.92
 [5,] 2.46 2.39 2.44 2.45 2.43 2.47 2.50 2.43 2.39  2.53  2.94
 [6,] 2.43 2.40 2.42 2.43 2.44 2.48 2.50 2.42 2.38  2.57  2.95
 [7,] 2.44 2.39 2.44 2.44 2.43 2.49 2.50 2.43 2.37  2.56  2.98
 [8,] 2.44 2.40 2.42 2.45 2.44 2.50 2.48 2.45 2.37  2.57  3.02
 [9,] 2.43 2.41 2.42 2.46 2.43 2.51 2.49 2.45 2.38  2.58  3.16
[10,] 2.43 2.41 2.42 2.44 2.44 2.49 2.48 2.46 2.39  2.57  3.20
[11,] 2.42 2.41 2.43 2.43 2.44 2.49 2.50 2.44 2.41  2.60  3.18
[12,] 2.43 2.41 2.44 2.42 2.43 2.48 2.50 2.45 2.42  2.63  3.17
> 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] 2.441667 2.408333 2.428333 2.440000 2.430000 2.470000 2.492500 2.452500
 [9] 2.398333 2.561667 2.997500
> arr.sd
 [1] 0.014034589 0.011934163 0.008348471 0.011281521 0.010444659 0.029541958
 [7] 0.009653073 0.020943647 0.024058011 0.037376058 0.152978014
> arr.range
 [1] 0.04 0.04 0.02 0.04 0.03 0.08 0.02 0.07 0.08 0.15 0.48
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    -0.5687       0.2393  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -14.45          11.47  

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

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

Coefficients:
(Intercept)     arr.mean  
    -1.8019       0.7584  

> postscript(file="/var/www/html/rcomp/tmp/17s081264553278.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/2mn9c1264553278.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/34z7h1264553278.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4y4591264553278.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/50c2a1264553278.tab") 
> 
> try(system("convert tmp/17s081264553278.ps tmp/17s081264553278.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mn9c1264553278.ps tmp/2mn9c1264553278.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.539   0.301   9.524