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(91.98,91.72,90.27,91.89,92.07,92.92,93.34,93.60,92.41,93.60,93.77,93.60,93.60,93.51,92.66,94.20,94.37,94.45,94.62,94.37,93.43,94.79,94.88,94.79,94.62,94.71,93.77,95.73,95.99,95.82,95.47,95.82,94.71,96.33,96.50,96.16,96.33,96.33,95.05,96.84,96.92,97.44,97.78,97.69,96.67,98.29,98.20,98.71,98.54,98.20,96.92,99.06,99.65,99.82,99.99,100.33,99.31,101.10,101.10,100.93,100.85,100.93,99.60,101.88,101.81,102.38,102.74,102.82,101.72,103.47,102.98,102.68,102.90,103.03,101.29,103.69,103.68,104.20,104.08,104.16,103.05,104.66,104.46,104.95,105.85,106.23,104.86,107.44,108.23,108.45,109.39,110.15,109.13,110.28,110.17,109.99,109.26,109.11,107.06,109.53,108.92,109.24,109.12,109.00,107.23,109.49,109.04,109.02)
> 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,] 91.98 93.60 94.62 96.33  98.54 100.85 102.90 105.85 109.26
 [2,] 91.72 93.51 94.71 96.33  98.20 100.93 103.03 106.23 109.11
 [3,] 90.27 92.66 93.77 95.05  96.92  99.60 101.29 104.86 107.06
 [4,] 91.89 94.20 95.73 96.84  99.06 101.88 103.69 107.44 109.53
 [5,] 92.07 94.37 95.99 96.92  99.65 101.81 103.68 108.23 108.92
 [6,] 92.92 94.45 95.82 97.44  99.82 102.38 104.20 108.45 109.24
 [7,] 93.34 94.62 95.47 97.78  99.99 102.74 104.08 109.39 109.12
 [8,] 93.60 94.37 95.82 97.69 100.33 102.82 104.16 110.15 109.00
 [9,] 92.41 93.43 94.71 96.67  99.31 101.72 103.05 109.13 107.23
[10,] 93.60 94.79 96.33 98.29 101.10 103.47 104.66 110.28 109.49
[11,] 93.77 94.88 96.50 98.20 101.10 102.98 104.46 110.17 109.04
[12,] 93.60 94.79 96.16 98.71 100.93 102.68 104.95 109.99 109.02
> 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]  92.59750  94.13917  95.46917  97.18750  99.57917 101.98833 103.67917
[8] 108.34750 108.83500
> arr.sd
[1] 1.0629130 0.6883110 0.8327005 1.0324563 1.2663940 1.0997011 0.9992038
[8] 1.8692202 0.8118945
> arr.range
[1] 3.50 2.22 2.73 3.66 4.18 3.87 3.66 5.42 2.47
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -1.61051      0.02679  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -9.677          2.108  

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

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

Coefficients:
(Intercept)     arr.mean  
   -3.02283      0.06533  

> postscript(file="/var/www/html/rcomp/tmp/1vege1259944030.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/2lp6k1259944030.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/3ako31259944030.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4nc7d1259944030.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/55ctt1259944030.tab") 
> system("convert tmp/1vege1259944030.ps tmp/1vege1259944030.png")
> system("convert tmp/2lp6k1259944030.ps tmp/2lp6k1259944030.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.513   0.289   0.597