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(321.935,310.215,309.030,305.333,294.735,289.351,288.225,289.648,290.155,288.301,289.148,289.741,287.595,285.226,287.816,283.519,290.304,282.166,280.041,282.500,279.913,277.793,281.229,275.363,273.547,270.601,273.338,271.917,273.985,273.911,270.798,271.115,271.344,274.525,276.663,273.784,274.027,269.160,270.491,270.846,270.333,272.599,272.764,270.674,268.175,268.351,272.482,268.714,269.419,265.518,264.101,267.179,271.322,270.157,271.296,269.907,271.244,266.844,270.911,269.829,269.285,263.018,266.680,265.814,268.457,269.508,270.223,264.676,265.521,262.971,266.003,267.722,266.433)
> 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] 73
> (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]
[1,] 321.935 294.735 290.155 287.595 290.304 279.913 273.547 273.985 271.344
[2,] 310.215 289.351 288.301 285.226 282.166 277.793 270.601 273.911 274.525
[3,] 309.030 288.225 289.148 287.816 280.041 281.229 273.338 270.798 276.663
[4,] 305.333 289.648 289.741 283.519 282.500 275.363 271.917 271.115 273.784
       [,10]   [,11]   [,12]   [,13]   [,14]   [,15]   [,16]   [,17]   [,18]
[1,] 274.027 270.333 268.175 269.419 271.322 271.244 269.285 268.457 265.521
[2,] 269.160 272.599 268.351 265.518 270.157 266.844 263.018 269.508 262.971
[3,] 270.491 272.764 272.482 264.101 271.296 270.911 266.680 270.223 266.003
[4,] 270.846 270.674 268.714 267.179 269.907 269.829 265.814 264.676 267.722
> 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] 311.6282 290.4898 289.3363 286.0390 283.7527 278.5745 272.3508 272.4522
 [9] 274.0790 271.1310 271.5925 269.4305 266.5542 270.6705 269.7070 266.1993
[17] 268.2160 265.5543
> arr.sd
 [1] 7.1788450 2.8957748 0.8044366 2.0485958 4.5012266 2.5666078 1.3730065
 [8] 1.7322485 2.1941758 2.0625617 1.2669434 2.0466741 2.2868723 0.7443827
[15] 2.0019689 2.5833920 2.4689400 1.9642473
> arr.range
 [1] 16.602  6.510  1.854  4.297 10.263  5.866  2.946  3.187  5.319  4.867
[11]  2.431  4.307  5.318  1.415  4.400  6.267  5.547  4.751
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  -21.04467      0.08468  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -31.970          5.816  

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

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

Coefficients:
(Intercept)     arr.mean  
   -48.7839       0.1957  

> postscript(file="/var/www/html/rcomp/tmp/19rh01244122355.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/2sn251244122355.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/3e8861244122355.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/46a6d1244122355.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5q4jx1244122355.tab") 
> 
> system("convert tmp/19rh01244122355.ps tmp/19rh01244122355.png")
> system("convert tmp/2sn251244122355.ps tmp/2sn251244122355.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.513   0.292   0.808