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(22577.0,22792.0,23932.0,22321.0,21102.0,22824.0,23129.0,23604.0,24746.0,26911.0,27909.0,28922.0,29800.0,30506.0,30771.0,31976.0,33749.0,34371.0,33246.0,35072.0,35762.0,36179.0,37433.0,38298.0,37559.0,37511.0,39364.0,40084.0,42712.0,41938.0,40799.0,38568.0,41134.0,43955.0,43607.0,45082.0,46464.0,46496.0,46774.0,47890.0,45740.0,42660.0,39190.0,39010.0,41150.0,42530.0,44710.0,46620.0,44560.0,46120.0,48060.0,51970.0,57720.0,63490.0,65370.0,64260.0,58700.0,58630.0,59803.0,59266.0,60570.0,63062.0,63846.0,64726.0,63460.0,65220.0,66659.0,66871.0,65672.0,67182.0,68292.0,68318.0,69530.0,70500.0,72044.0,73811.0,76018.0,77818.0,79455.0,81408.0,81815.0)
> 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] 81
> (np <- floor(n / par1))
[1] 20
> 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,] 22577 21102 24746 29800 33749 35762 37559 42712 41134 46464 45740 41150
[2,] 22792 22824 26911 30506 34371 36179 37511 41938 43955 46496 42660 42530
[3,] 23932 23129 27909 30771 33246 37433 39364 40799 43607 46774 39190 44710
[4,] 22321 23604 28922 31976 35072 38298 40084 38568 45082 47890 39010 46620
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,] 44560 57720 58700 60570 63460 65672 69530 76018
[2,] 46120 63490 58630 63062 65220 67182 70500 77818
[3,] 48060 65370 59803 63846 66659 68292 72044 79455
[4,] 51970 64260 59266 64726 66871 68318 73811 81408
> 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] 22905.50 22664.75 27122.00 30763.25 34109.50 36918.00 38629.50 41004.25
 [9] 43444.50 46906.00 41650.00 43752.50 47677.50 62710.00 59099.75 63051.00
[17] 65552.50 67366.00 71471.25 78674.75
> arr.sd
 [1]  710.9001 1090.1478 1784.1213  906.4309  789.5950 1162.1936 1297.6996
 [8] 1804.2303 1664.0145  670.6077 3202.5719 2408.7947 3199.8164 3414.9963
[15]  548.5328 1788.2144 1576.0602 1247.3000 1872.0978 2300.1295
> arr.range
 [1] 1611 2502 4176 2176 1826 2536 2573 4144 3948 1426 6730 5470 7410 7650 1173
[16] 4156 3411 2646 4281 5390
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  891.51273      0.01651  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       1.8347         0.5098  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.997e+03    3.734e-02  

> postscript(file="/var/www/html/rcomp/tmp/1il371274880567.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/26ad41274880567.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/39aus1274880567.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4vbsf1274880567.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5ytql1274880567.tab") 
> 
> try(system("convert tmp/1il371274880567.ps tmp/1il371274880567.png",intern=TRUE))
character(0)
> try(system("convert tmp/26ad41274880567.ps tmp/26ad41274880567.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.522   0.298   0.725