R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-redhat-linux-gnu (64-bit)

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> x <- c(97,100.7,101.4,101.5,101.8,101.5,102.2,101.8,98.5,98.4,97.5,97.7,98.3,99.6,99.4,96.7,96.9,96.1,97.9,99.2,97.8,94.9,93.3,91.5,89.1,92.3,91.8,92.1,94.4,92.8,92.6,92.3,92.1,89.8,87.4,87.7,86.3,89.1,90.4,87.1,86.7,84.4,88.4,88.9,88.5,87.2,86.2,83.4,87.5,85.7,87.4,86.8,87.9,85.9,87.7,87,86.8,86.2,86.1,87.5,85.7,88.9,89.8,91.4,95.2,94.1,96.8,96.1,96.6,94.2,93.9,96.5,93.4,95,95.2,94,97,96.9,96.3,96.3,97.3,95.7,96.4,95.1,94.6,95.9,96.2,94.3,98.3,95.9,92.1,94.6,94.7,96.7,97.5,96.2,97.1,95.9,94.5,99.4,101.3,101.4,100.9,101.4,103.1,102.4,101.1,102,103.9,101.7,101.2,101.9,101.1,103.1,103.3,101.4,102.8,103,102.6,102.2)
> 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] 120
> (np <- floor(n / par1))
[1] 10
> 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]
 [1,]  97.0 98.3 89.1 86.3 87.5 85.7 93.4 94.6  97.1 103.9
 [2,] 100.7 99.6 92.3 89.1 85.7 88.9 95.0 95.9  95.9 101.7
 [3,] 101.4 99.4 91.8 90.4 87.4 89.8 95.2 96.2  94.5 101.2
 [4,] 101.5 96.7 92.1 87.1 86.8 91.4 94.0 94.3  99.4 101.9
 [5,] 101.8 96.9 94.4 86.7 87.9 95.2 97.0 98.3 101.3 101.1
 [6,] 101.5 96.1 92.8 84.4 85.9 94.1 96.9 95.9 101.4 103.1
 [7,] 102.2 97.9 92.6 88.4 87.7 96.8 96.3 92.1 100.9 103.3
 [8,] 101.8 99.2 92.3 88.9 87.0 96.1 96.3 94.6 101.4 101.4
 [9,]  98.5 97.8 92.1 88.5 86.8 96.6 97.3 94.7 103.1 102.8
[10,]  98.4 94.9 89.8 87.2 86.2 94.2 95.7 96.7 102.4 103.0
[11,]  97.5 93.3 87.4 86.2 86.1 93.9 96.4 97.5 101.1 102.6
[12,]  97.7 91.5 87.7 83.4 87.5 96.5 95.1 96.2 102.0 102.2
> 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] 100.00000  96.80000  91.20000  87.21667  86.87500  93.26667  95.71667
 [8]  95.58333 100.04167 102.35000
> arr.sd
 [1] 1.9913449 2.5096179 2.1788237 2.0049182 0.7509085 3.5625153 1.2126855
 [8] 1.6447345 2.7437394 0.9040314
> arr.range
 [1]  5.2  8.1  7.0  7.0  2.2 11.1  3.9  6.2  8.6  2.8
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   1.021002     0.009792  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -3.6487         0.9262  

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

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

Coefficients:
(Intercept)     arr.mean  
   6.724522    -0.005421  

> postscript(file="/var/www/wessaorg/rcomp/tmp/1mf7m1294248303.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/wessaorg/rcomp/tmp/2p93x1294248303.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/wessaorg/rcomp/tmp/3h08m1294248303.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/wessaorg/rcomp/tmp/4k65v1294248303.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/wessaorg/rcomp/tmp/54ym21294248303.tab") 
> 
> try(system("convert tmp/1mf7m1294248303.ps tmp/1mf7m1294248303.png",intern=TRUE))
character(0)
> try(system("convert tmp/2p93x1294248303.ps tmp/2p93x1294248303.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   0.60    0.15    0.77