R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(10.81,9.12,11.03,12.74,9.98,11.62,9.40,9.27,7.76,8.78,10.65,10.95,12.36,10.85,11.84,12.14,11.65,8.86,7.63,7.38,7.25,8.03,7.75,7.16,7.18,7.51,7.07,7.11,8.98,9.53,10.54,11.31,10.36,11.44,10.45,10.69,11.28,11.96,13.52,12.89,14.03,16.27,16.17,17.25,19.38,26.20,33.53,32.20,38.45,44.86,41.67,36.06,39.76,36.81,42.65,46.89,53.61,57.59,67.82,71.89,75.51,68.49,62.72,70.39,59.77,57.27,67.96,67.85,76.98,81.08,91.66,84.84,85.73,84.61,92.91,99.80,121.19,122.04,131.76,138.48,153.47,189.95,182.22,198.08,135.36,125.02,143.50,173.95,188.75,167.44,158.95,169.53,113.66,107.59,92.67,85.35,90.13,89.31,105.12,125.83,135.81,142.43,163.39,168.21,185.35,188.50,199.91,210.73,192.06,204.62,235.00,261.09,256.88,251.53,257.25,243.10,283.75)
> 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] 117
> (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,] 10.81 12.36  7.18 11.28 38.45 75.51  85.73 135.36  90.13
 [2,]  9.12 10.85  7.51 11.96 44.86 68.49  84.61 125.02  89.31
 [3,] 11.03 11.84  7.07 13.52 41.67 62.72  92.91 143.50 105.12
 [4,] 12.74 12.14  7.11 12.89 36.06 70.39  99.80 173.95 125.83
 [5,]  9.98 11.65  8.98 14.03 39.76 59.77 121.19 188.75 135.81
 [6,] 11.62  8.86  9.53 16.27 36.81 57.27 122.04 167.44 142.43
 [7,]  9.40  7.63 10.54 16.17 42.65 67.96 131.76 158.95 163.39
 [8,]  9.27  7.38 11.31 17.25 46.89 67.85 138.48 169.53 168.21
 [9,]  7.76  7.25 10.36 19.38 53.61 76.98 153.47 113.66 185.35
[10,]  8.78  8.03 11.44 26.20 57.59 81.08 189.95 107.59 188.50
[11,] 10.65  7.75 10.45 33.53 67.82 91.66 182.22  92.67 199.91
[12,] 10.95  7.16 10.69 32.20 71.89 84.84 198.08  85.35 210.73
> 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]  10.175833   9.408333   9.347500  18.723333  48.171667  72.043333 133.353333
[8] 138.480833 150.393333
> arr.sd
[1]  1.380932  2.155993  1.709099  7.723485 12.035228 10.322289 40.334396
[8] 33.998239 42.152117
> arr.range
[1]   4.98   5.20   4.37  22.25  35.83  34.39 113.47 103.40 121.42
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    -1.1808       0.2753  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -1.790          1.087  

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

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

Coefficients:
(Intercept)     arr.mean  
    -3.0912       0.8018  

> postscript(file="/var/www/rcomp/tmp/1hgvz1292343622.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/rcomp/tmp/2hgvz1292343622.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/33ybn1292343622.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4ozsb1292343622.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/rcomp/tmp/5rh8z1292343622.tab") 
> 
> try(system("convert tmp/1hgvz1292343622.ps tmp/1hgvz1292343622.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hgvz1292343622.ps tmp/2hgvz1292343622.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.540   0.440   0.982