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(100.7,105.9,115.4,113.9,121.5,119.5,115.8,116.3,113.5,110.7,116.9,141.1,101.8,102.9,119,112.8,120.9,123.1,121.9,119.4,110.9,116.8,120.6,143.3,106.4,106.9,125.6,110.9,127,124.3,121.3,124.4,113.2,120.2,122.6,143.3,106.5,105.9,114,121.6,119.7,122.5,126.5,118.2,115.5,120.1,115.3,146.5,107.7,106.3,121.8,115.8,115.4,124.3,121.7,118.7,113.5,113.4,115.1,144.2,100.9,103.2,121.3,111.9,117.3,124.2,122,119.6,114.9,112.2,115.3,143,104,105.3,124.3,114.1,124.8,131.9,125.8,125.2,119.8,116.2,120.2,148.6,109.4,109.6,135.2,115.2,129.1,138.8,126,130.7,120.5,126.5,128,151.7,114.8,118.9,131.5,124.8,137,137.1,137,131.3,126,129.7,125.1,157.8)
> 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] 108
> (np <- floor(n / par1))
[1] 9
> 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]
 [1,] 100.7 101.8 106.4 106.5 107.7 100.9 104.0 109.4 114.8
 [2,] 105.9 102.9 106.9 105.9 106.3 103.2 105.3 109.6 118.9
 [3,] 115.4 119.0 125.6 114.0 121.8 121.3 124.3 135.2 131.5
 [4,] 113.9 112.8 110.9 121.6 115.8 111.9 114.1 115.2 124.8
 [5,] 121.5 120.9 127.0 119.7 115.4 117.3 124.8 129.1 137.0
 [6,] 119.5 123.1 124.3 122.5 124.3 124.2 131.9 138.8 137.1
 [7,] 115.8 121.9 121.3 126.5 121.7 122.0 125.8 126.0 137.0
 [8,] 116.3 119.4 124.4 118.2 118.7 119.6 125.2 130.7 131.3
 [9,] 113.5 110.9 113.2 115.5 113.5 114.9 119.8 120.5 126.0
[10,] 110.7 116.8 120.2 120.1 113.4 112.2 116.2 126.5 129.7
[11,] 116.9 120.6 122.6 115.3 115.1 115.3 120.2 128.0 125.1
[12,] 141.1 143.3 143.3 146.5 144.2 143.0 148.6 151.7 157.8
> 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] 115.9333 117.7833 120.5083 119.3583 118.1583 117.1500 121.6833 126.7250
[9] 130.9167
> arr.sd
[1]  9.763600 10.737431 10.234119 10.492894  9.811168 10.803661 11.867437
[8] 12.173079 11.022690
> arr.range
[1] 40.4 41.5 36.9 40.6 37.9 42.1 44.6 42.3 43.0
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    -1.6159       0.1024  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -3.261          1.175  

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

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

Coefficients:
(Intercept)     arr.mean  
    16.9965       0.1988  

> postscript(file="/var/www/html/rcomp/tmp/1mly91263303879.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/27lg31263303879.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/3xne31263303879.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/46d6y1263303879.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5p1rw1263303879.tab") 
> 
> try(system("convert tmp/1mly91263303879.ps tmp/1mly91263303879.png",intern=TRUE))
character(0)
> try(system("convert tmp/27lg31263303879.ps tmp/27lg31263303879.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.504   0.291   0.744