R version 2.6.2 (2008-02-08)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(430.00,433.87,434.55,434.55,434.55,434.55,434.71,434.71,434.71,434.71,434.73,436.34,437.55,439.58,439.65,439.76,439.76,439.76,440.06,440.13,441.18,441.14,441.14,441.19,449.06,456.46,456.79,456.87,457.25,455.93,456.00,456.22,456.22,456.58,457.61,457.61,460.43,460.43,462.18,462.37,462.59,463.19,463.48,464.30,461.41,463.35,463.35,463.35,464.27,472.28,472.36,472.56,472.56,472.56,474.15,474.59,474.97,474.99,474.99,474.99,478.34,485.70,485.75,485.85,485.84,485.85,485.84,486.00,488.79,489.71,489.71,489.71)
> 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] 72
> (np <- floor(n / par1))
[1] 18
> 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,] 430.00 434.55 434.71 437.55 439.76 441.18 449.06 457.25 456.22 460.43
[2,] 433.87 434.55 434.71 439.58 439.76 441.14 456.46 455.93 456.58 460.43
[3,] 434.55 434.71 434.73 439.65 440.06 441.14 456.79 456.00 457.61 462.18
[4,] 434.55 434.71 436.34 439.76 440.13 441.19 456.87 456.22 457.61 462.37
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]
[1,] 462.59 461.41 464.27 472.56 474.97 478.34 485.84 488.79
[2,] 463.19 463.35 472.28 472.56 474.99 485.70 485.85 489.71
[3,] 463.48 463.35 472.36 474.15 474.99 485.75 485.84 489.71
[4,] 464.30 463.35 472.56 474.59 474.99 485.85 486.00 489.71
> 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] 433.2425 434.6300 435.1225 439.1350 439.9275 441.1625 454.7950 456.3500
 [9] 457.0050 461.3525 463.3900 462.8650 470.3675 473.4650 474.9850 483.9100
[17] 485.8825 489.4800
> arr.sd
 [1] 2.18530509 0.09237604 0.81172142 1.05926075 0.19551215 0.02629956
 [7] 3.82744911 0.61259013 0.71388608 1.06803168 0.71091490 0.97000000
[13] 4.06670526 1.06033014 0.01000000 3.71385693 0.07847505 0.46000000
> arr.range
 [1] 4.55 0.16 1.63 2.21 0.37 0.05 7.81 1.32 1.39 1.94 1.71 1.94 8.29 2.03 0.02
[16] 7.51 0.16 0.92
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -3.77755      0.01086  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -7.826          1.169  

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

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

Coefficients:
(Intercept)     arr.mean  
   -7.29859      0.02124  

> postscript(file="/var/www/html/rcomp/tmp/12g6f1211119218.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/2bwz81211119218.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/3bz3k1211119218.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4eb3b1211119218.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/53mzw1211119218.tab") 
> 
> system("convert tmp/12g6f1211119218.ps tmp/12g6f1211119218.png")
> system("convert tmp/2bwz81211119218.ps tmp/2bwz81211119218.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.740   0.295   0.944