R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(67.8,66.9,71.5,75.9,71.9,70.7,73.5,76.1,82.5,87.1,83.2,86.1,85.9,77.4,74.4,69.9,73.8,69.2,69.7,71,71.2,75.8,73,66.4,58.6,55.5,52.6,54.9,54.6,51.2,50.9,49.6,53.4,52,47.5,42.1,44.5,43.2,51.4,59.4,60.3,61.4,68.8,73.6,81.8,79.6,85.8,88.1,89.1,95,96.2,84.2,96.9,103.1,99.3,103.5,112.4,111.1,113.7,92,93,98.4,92.6,94.6,99.5,97.6,91.3,93.6,93.1,78.4,70.2,69.3,71.1,73.5,85.9,91.5,91.8,88.3,91.3,94,99.3,96.7,88,96.7,106.8,114.3,105.7,90.1,91.6,97.7,100.8,104.6,95.9,102.7,104,107.9,113.8,113.8,123.1,125.1,137.6,134,140.3,152.1,150.6,167.3,153.2,142,154.4,158.5,180.9,181.3,172.4,192,199.3,215.4,214.3,201.5,190.5,196,215.7,209.4,214.1,237.8,239,237.8,251.5,248.8,215.4,201.2,203.1,214.2,188.9,203,213.3,228.5,228.2,240.9,258.8,248.5,269.2,289.6,323.4,317.2,322.8,340.9,368.2,388.5,441.2,474.3,483.9,417.9,365.9,263,199.4)
> 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] 155
> (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,] 67.8 85.9 58.6 44.5  89.1 93.0 71.1 106.8 113.8 154.4 215.7 188.9
 [2,] 66.9 77.4 55.5 43.2  95.0 98.4 73.5 114.3 113.8 158.5 209.4 203.0
 [3,] 71.5 74.4 52.6 51.4  96.2 92.6 85.9 105.7 123.1 180.9 214.1 213.3
 [4,] 75.9 69.9 54.9 59.4  84.2 94.6 91.5  90.1 125.1 181.3 237.8 228.5
 [5,] 71.9 73.8 54.6 60.3  96.9 99.5 91.8  91.6 137.6 172.4 239.0 228.2
 [6,] 70.7 69.2 51.2 61.4 103.1 97.6 88.3  97.7 134.0 192.0 237.8 240.9
 [7,] 73.5 69.7 50.9 68.8  99.3 91.3 91.3 100.8 140.3 199.3 251.5 258.8
 [8,] 76.1 71.0 49.6 73.6 103.5 93.6 94.0 104.6 152.1 215.4 248.8 248.5
 [9,] 82.5 71.2 53.4 81.8 112.4 93.1 99.3  95.9 150.6 214.3 215.4 269.2
[10,] 87.1 75.8 52.0 79.6 111.1 78.4 96.7 102.7 167.3 201.5 201.2 289.6
[11,] 83.2 73.0 47.5 85.8 113.7 70.2 88.0 104.0 153.2 190.5 203.1 323.4
[12,] 86.1 66.4 42.1 88.1  92.0 69.3 96.7 107.9 142.0 196.0 214.2 317.2
> 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]  76.10000  73.14167  51.90833  66.49167  99.70833  89.30000  89.00833
 [8] 101.84167 137.74167 188.04167 224.00000 250.79167
> arr.sd
 [1]  7.010771  5.060625  4.254080 15.580317  9.378356 10.569940  8.742837
 [8]  7.010960 16.633616 19.485401 17.796527 42.875898
> arr.range
 [1]  20.2  19.5  16.5  44.9  29.5  30.2  28.2  24.2  53.5  61.0  50.3 134.5
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    -2.6557       0.1355  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -2.704          1.094  

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

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

Coefficients:
(Intercept)     arr.mean  
    -6.9959       0.4119  

> postscript(file="/var/www/html/rcomp/tmp/1gdlu1228754506.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/2omgv1228754506.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/3y0bk1228754506.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/453sw1228754506.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5ypv01228754507.tab") 
> 
> system("convert tmp/1gdlu1228754506.ps tmp/1gdlu1228754506.png")
> system("convert tmp/2omgv1228754506.ps tmp/2omgv1228754506.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.833   0.768   1.944