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(771.28,766.78,757.59,747.73,746.59,744.5,744.29,743.79,738.89,736.74,732.77,731.58,731.48,730.08,724.19,716.81,714.84,713.18,713.16,713.15,713.6,707.08,704.11,704.36,704.36,701.93,696.44,686.58,684.48,683.74,683.7,683.52,678.77,674.71,670.28,668.85,668.85,669.35,672.28,671.6,671.96,671.18,671.18,681.14,682.23,679.98,679.69,679.69,679.7,681.21,672.32,669.98,667.91,666.04,666.04,666.27,664.45,660.76,660.4,660.69,660.69,662.23,661.41,659.02,655.43,652.59,652.59,648.2,645.84,644.67,642.71,640.14,640.14,639.64,630.28,614.57,614.7,615.08,615.08,614.43,604.55,598.98,594.05,593.05,593.05,593.34,584.72,580.7,577.08,569.92,569.92,568.86,559.38,548.22,545.61,545.33)
> 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] 96
> (np <- floor(n / par1))
[1] 24
> 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]
[1,] 771.28 746.59 738.89 731.48 714.84 713.60 704.36 684.48 678.77 668.85
[2,] 766.78 744.50 736.74 730.08 713.18 707.08 701.93 683.74 674.71 669.35
[3,] 757.59 744.29 732.77 724.19 713.16 704.11 696.44 683.70 670.28 672.28
[4,] 747.73 743.79 731.58 716.81 713.15 704.36 686.58 683.52 668.85 671.60
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
[1,] 671.96 682.23 679.70 667.91 664.45 660.69 655.43 645.84 640.14 614.70
[2,] 671.18 679.98 681.21 666.04 660.76 662.23 652.59 644.67 639.64 615.08
[3,] 671.18 679.69 672.32 666.04 660.40 661.41 652.59 642.71 630.28 615.08
[4,] 681.14 679.69 669.98 666.27 660.69 659.02 648.20 640.14 614.57 614.43
      [,21]  [,22]  [,23]  [,24]
[1,] 604.55 593.05 577.08 559.38
[2,] 598.98 593.34 569.92 548.22
[3,] 594.05 584.72 569.92 545.61
[4,] 593.05 580.70 568.86 545.33
> 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] 760.8450 744.7925 734.9950 725.6400 713.5825 707.2875 697.3275 683.8600
 [9] 673.1525 670.5200 673.8650 680.3975 675.8025 666.5650 661.5750 660.8375
[17] 652.2025 643.3400 631.1575 614.8225 597.6575 587.9525 571.4450 549.6350
> arr.sd
 [1] 10.4357031  1.2347841  3.4072912  6.6805838  0.8384261  4.4180492
 [7]  7.8937839  0.4242641  4.4998102  1.6754900  4.8639182  1.2292918
[13]  5.4912316  0.9031980  1.9229925  1.3652686  2.9853573  2.4937121
[19] 11.9520330  0.3171093  5.2756887  6.2731564  3.7897537  6.6257301
> arr.range
 [1] 23.55  2.80  7.31 14.67  1.69  9.49 17.78  0.96  9.92  3.43  9.96  2.54
[13] 11.23  1.87  4.05  3.21  7.23  5.70 25.57  0.65 11.50 12.64  8.22 14.05
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   5.614860    -0.002363  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
        7.427         -0.985  

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

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

Coefficients:
(Intercept)     arr.mean  
  10.124626    -0.002063  

> postscript(file="/var/www/rcomp/tmp/15wqt1291842867.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/25wqt1291842867.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/3j6nk1291842867.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4m7m71291842867.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5q7kv1291842867.tab") 
> 
> try(system("convert tmp/15wqt1291842867.ps tmp/15wqt1291842867.png",intern=TRUE))
character(0)
> try(system("convert tmp/25wqt1291842867.ps tmp/25wqt1291842867.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.600   0.190   0.778