R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(5740,5639,5538,5336,7380,7279,5740,4718,4819,4819,4920,5133,4516,3898,3392,3392,5336,5538,3999,2258,3179,3179,3898,4313,4212,3179,3696,3493,5234,4819,3179,1954,3078,3392,3696,4100,3280,2572,2876,2977,5639,5639,4100,3898,4516,4212,5032,6054,6257,4819,4414,3999,6773,6976,6459,6976,6874,6054,6976,7998,8413,7178,6358,6976,9638,10458,10256,10660,10559,9537,11278,11693,12300,10458,9739,10559,12513,14254,13839,13839,14042,13333,15176,15176,14862,13120,13434,13637,14973,16714,15479,16097,15580,15277,17636,17119,16400,15378,16400,16917,17534,18354,17534,18040,17423,17322,19883,20096,19276,17838,19063,19579,20197,21118,20197,20916,20602,19478,21837,21837)
> 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] 120
> (np <- floor(n / par1))
[1] 30
> 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] [,13] [,14]
[1,] 5740 7380 4819 4516 5336 3179 4212 5234 3078  3280  5639  4516  6257  6773
[2,] 5639 7279 4819 3898 5538 3179 3179 4819 3392  2572  5639  4212  4819  6976
[3,] 5538 5740 4920 3392 3999 3898 3696 3179 3696  2876  4100  5032  4414  6459
[4,] 5336 4718 5133 3392 2258 4313 3493 1954 4100  2977  3898  6054  3999  6976
     [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26]
[1,]  6874  8413  9638 10559 12300 12513 14042 14862 14973 15580 16400 17534
[2,]  6054  7178 10458  9537 10458 14254 13333 13120 16714 15277 15378 18354
[3,]  6976  6358 10256 11278  9739 13839 15176 13434 15479 17636 16400 17534
[4,]  7998  6976 10660 11693 10559 13839 15176 13637 16097 17119 16917 18040
     [,27] [,28] [,29] [,30]
[1,] 17423 19276 20197 20602
[2,] 17322 17838 21118 19478
[3,] 19883 19063 20197 21837
[4,] 20096 19579 20916 21837
> 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]  5563.25  6279.25  4922.75  3799.50  4282.75  3642.25  3645.00  3796.50
 [9]  3566.50  2926.25  4819.00  4953.50  4872.25  6796.00  6975.50  7231.25
[17] 10253.00 10766.75 10764.00 13611.25 14431.75 13763.25 15815.75 16403.00
[25] 16273.75 17865.50 18681.00 18939.00 20607.00 20938.50
> arr.sd
 [1]  172.4903 1283.1527  148.0324  533.9123 1512.7365  561.1045  433.7242
 [8] 1515.2585  436.0715  291.9662  950.4388  807.9792  981.9923  244.1980
[15]  796.8628  861.6045  441.9306  944.2388 1087.1342  757.8524  906.8210
[22]  762.7509  754.8913 1151.5424  644.9849  403.6777 1513.9875  763.9254
[29]  480.5559 1134.4451
> arr.range
 [1]  404 2662  314 1124 3280 1134 1033 3280 1022  708 1741 1842 2258  517 1944
[16] 2055 1022 2156 2561 1741 1843 1742 1741 2359 1539  820 2774 1741  921 2359
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  668.53200      0.01085  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
        4.333          0.241  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.516e+03    1.734e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/1s5po1312388522.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/wessaorg/rcomp/tmp/2pya81312388522.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/31n5x1312388522.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/41uni1312388522.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/wessaorg/rcomp/tmp/5nw1j1312388522.tab") 
> 
> try(system("convert tmp/1s5po1312388522.ps tmp/1s5po1312388522.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pya81312388522.ps tmp/2pya81312388522.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.643   0.162   0.850