R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(138.1,138.6,160.8,151.5,142.7,157.4,138.9,141.0,150.9,149.9,153.0,144.3,128.1,123.3,155.9,144.1,134.1,153.1,131.0,129.8,139.9,135.6,126.8,134.4,113.5,107.5,133.8,119.0,125.9,130.1,114.2,111.6,131.2,124.1,127.1,123.4,100.7,100.3,121.6,110.5,110.3,122.7,102.6,101.8,113.6,107.2,116.8,112.5,89.0,95.2,110.6,102.6,106.4,112.7,103.2,104.2,111.3,115.7,111.6,112.2,92.2,97.1,108.1,107.2,107.2,110.3,97.6,100.6,102.8,105.3,109.5,105.7,93.7,91.7,111.6,109.2,101.2,114.3,100.9,106.0,109.0,110.4,110.7,105.7,89.6,83.1,103.5,104.8,93.5,106.7,93.7,84.7,99.2,91.9,94.9,94.1,80.8,72.6,94.0,80.0,85.4,91.5,76.1,76.1,89.5,85.3,91.0,93.0,73.4,76.6,95.0,84.5,88.7,93.1,83.4,82.2,95.6,83.7,94.3,93.0,71.8,75.3,91.8,80.7,84.8,83.1,78.4,78.7,84.7,80.5,91.8,83.5,66.6,68.6,83.6,79.7,79.9,81.2,74.3,73.0,78.8,81.6,85.0,91.1,68.2,59.8,83.1,76.7,73.2,83.9,73.0,70.9)
> 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] 152
> (np <- floor(n / par1))
[1] 12
> 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]
 [1,] 138.1 128.1 113.5 100.7  89.0  92.2  93.7  89.6 80.8  73.4  71.8  66.6
 [2,] 138.6 123.3 107.5 100.3  95.2  97.1  91.7  83.1 72.6  76.6  75.3  68.6
 [3,] 160.8 155.9 133.8 121.6 110.6 108.1 111.6 103.5 94.0  95.0  91.8  83.6
 [4,] 151.5 144.1 119.0 110.5 102.6 107.2 109.2 104.8 80.0  84.5  80.7  79.7
 [5,] 142.7 134.1 125.9 110.3 106.4 107.2 101.2  93.5 85.4  88.7  84.8  79.9
 [6,] 157.4 153.1 130.1 122.7 112.7 110.3 114.3 106.7 91.5  93.1  83.1  81.2
 [7,] 138.9 131.0 114.2 102.6 103.2  97.6 100.9  93.7 76.1  83.4  78.4  74.3
 [8,] 141.0 129.8 111.6 101.8 104.2 100.6 106.0  84.7 76.1  82.2  78.7  73.0
 [9,] 150.9 139.9 131.2 113.6 111.3 102.8 109.0  99.2 89.5  95.6  84.7  78.8
[10,] 149.9 135.6 124.1 107.2 115.7 105.3 110.4  91.9 85.3  83.7  80.5  81.6
[11,] 153.0 126.8 127.1 116.8 111.6 109.5 110.7  94.9 91.0  94.3  91.8  85.0
[12,] 144.3 134.4 123.4 112.5 112.2 105.7 105.7  94.1 93.0  93.0  83.5  91.1
> 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] 147.25833 136.34167 121.78333 110.05000 106.22500 103.63333 105.36667
 [8]  94.97500  84.60833  86.95833  82.09167  78.61667
> arr.sd
 [1]  7.715564 10.206723  8.512113  7.816242  7.896274  5.648867  7.141725
 [8]  7.471415  7.365331  7.468657  5.933642  6.972391
> arr.range
 [1] 94.2 87.3 50.2 43.0 35.8 29.1 40.0 33.7 15.2 15.1  6.8  7.6
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    4.06986      0.03284  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
     -0.06999        0.44797  

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

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

Coefficients:
(Intercept)     arr.mean  
    -96.378        1.284  

> postscript(file="/var/www/html/rcomp/tmp/1xbjy1196265133.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/24wxv1196265133.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 
> 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/34cie1196265134.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4hzix1196265134.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5ics31196265134.tab") 
> 
> system("convert tmp/1xbjy1196265133.ps tmp/1xbjy1196265133.png")
> system("convert tmp/24wxv1196265133.ps tmp/24wxv1196265133.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.759   0.289   0.856