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(27.00,26.88,27.38,26.82,27.00,26.15,25.85,26.17,25.66,25.72,25.42,25.10,26.20,26.39,26.27,26.63,21.10,20.30,20.61,21.05,20.45,20.91,21.22,20.85,21.90,22.71,22.40,22.81,23.96,23.37,23.55,23.01,22.63,22.63,22.00,22.15,22.00,22.00,21.84,22.10,22.37,21.83,21.77,21.89,20.76,20.21,20.19,20.01,19.16,18.50,17.41,18.14,18.60,18.32,18.40,18.16,17.29,16.65,16.36,16.32,17.37,17.30,18.10,19.00,18.38,18.41,18.10,17.87,18.70,18.81,18.88,19.44,18.60,18.80,18.62,18.24,17.84,17.85,17.67,17.99,18.15,18.39,18.07,18.39)
> par1 = '4'
> #'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] 84
> (np <- floor(n / par1))
[1] 21
> 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,] 27.00 27.00 25.66 26.20 21.10 20.45 21.90 23.96 22.63 22.00 22.37 20.76
[2,] 26.88 26.15 25.72 26.39 20.30 20.91 22.71 23.37 22.63 22.00 21.83 20.21
[3,] 27.38 25.85 25.42 26.27 20.61 21.22 22.40 23.55 22.00 21.84 21.77 20.19
[4,] 26.82 26.17 25.10 26.63 21.05 20.85 22.81 23.01 22.15 22.10 21.89 20.01
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
[1,] 19.16 18.60 17.29 17.37 18.38 18.70 18.60 17.84 18.15
[2,] 18.50 18.32 16.65 17.30 18.41 18.81 18.80 17.85 18.39
[3,] 17.41 18.40 16.36 18.10 18.10 18.88 18.62 17.67 18.07
[4,] 18.14 18.16 16.32 19.00 17.87 19.44 18.24 17.99 18.39
> 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] 27.0200 26.2925 25.4750 26.3725 20.7650 20.8575 22.4550 23.4725 22.3525
[10] 21.9850 21.9650 20.2925 18.3025 18.3700 16.6550 17.9425 18.1900 18.9575
[19] 18.5650 17.8375 18.2500
> arr.sd
 [1] 0.2513961 0.4938539 0.2816026 0.1887459 0.3802192 0.3163727 0.4091047
 [8] 0.3950000 0.3262284 0.1075484 0.2744085 0.3243840 0.7296746 0.1829390
[15] 0.4481443 0.7923962 0.2549510 0.3300884 0.2345918 0.1309898 0.1649242
> arr.range
 [1] 0.56 1.15 0.62 0.43 0.80 0.77 0.91 0.95 0.63 0.26 0.60 0.75 1.75 0.44 0.97
[16] 1.70 0.54 0.74 0.56 0.32 0.32
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   0.508767    -0.008288  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -0.5823        -0.2087  

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

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

Coefficients:
(Intercept)     arr.mean  
    1.11657     -0.01736  

> postscript(file="/var/www/html/rcomp/tmp/1yqta1243877933.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/2nq9n1243877933.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/3n4uo1243877933.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4b7hl1243877933.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/59l9o1243877933.tab") 
> 
> system("convert tmp/1yqta1243877933.ps tmp/1yqta1243877933.png")
> system("convert tmp/2nq9n1243877933.ps tmp/2nq9n1243877933.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.516   0.299   0.617