R version 2.6.2 (2008-02-08)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(513.13,513.13,513.13,513.13,513.13,513.13,513.13,513.13,513.13,527.96,527.96,527.96,527.96,527.96,527.96,527.96,527.96,527.96,527.96,527.96,527.96,536.61,536.61,536.61,536.61,536.61,536.61,536.61,536.61,536.61,536.61,536.61,536.61,545.06,545.06,545.06,545.06,545.06,545.06,545.06,545.06,545.06,545.06,545.06,545.06,564.24,564.24,564.24,564.24,564.24,564.24,564.24,564.24,564.24,564.24,564.24,564.24,573.68,573.68,573.68,573.68,573.68,573.68,573.68,573.68,573.68,573.68,573.68,573.68,576.3,576.29,576.29,576.29,576.29,576.29,576.29,576.29,576.3,576.29,576.3,576.29,589.85,589.85,589.85,589.85,589.85,589.85,589.85,589.85,589.85,589.85,589.85,589.85,599.12,599.12,599.12)
> 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] 96
> (np <- floor(n / par1))
[1] 8
> 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]
 [1,] 513.13 527.96 536.61 545.06 564.24 573.68 576.29 589.85
 [2,] 513.13 527.96 536.61 545.06 564.24 573.68 576.29 589.85
 [3,] 513.13 527.96 536.61 545.06 564.24 573.68 576.29 589.85
 [4,] 513.13 527.96 536.61 545.06 564.24 573.68 576.29 589.85
 [5,] 513.13 527.96 536.61 545.06 564.24 573.68 576.29 589.85
 [6,] 513.13 527.96 536.61 545.06 564.24 573.68 576.30 589.85
 [7,] 513.13 527.96 536.61 545.06 564.24 573.68 576.29 589.85
 [8,] 513.13 527.96 536.61 545.06 564.24 573.68 576.30 589.85
 [9,] 513.13 527.96 536.61 545.06 564.24 573.68 576.29 589.85
[10,] 527.96 536.61 545.06 564.24 573.68 576.30 589.85 599.12
[11,] 527.96 536.61 545.06 564.24 573.68 576.29 589.85 599.12
[12,] 527.96 536.61 545.06 564.24 573.68 576.29 589.85 599.12
> 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] 516.8375 530.1225 538.7225 549.8550 566.6000 574.3333 579.6817 592.1675
> arr.sd
[1] 6.707120 3.912110 3.821656 8.674481 4.269401 1.181927 6.131737 4.192515
> arr.range
[1] 14.83  8.65  8.45 19.18  9.44  2.62 13.56  9.27
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   18.71665     -0.02492  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       25.751         -3.845  

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

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

Coefficients:
(Intercept)     arr.mean  
   41.36523     -0.05506  

> postscript(file="/var/www/html/rcomp/tmp/10pc01210766798.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/2y6fw1210766798.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/36jyc1210766798.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4hs9y1210766798.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5h0mk1210766798.tab") 
> 
> system("convert tmp/10pc01210766798.ps tmp/10pc01210766798.png")
> system("convert tmp/2y6fw1210766798.ps tmp/2y6fw1210766798.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.712   0.266   0.823