R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(52347,52407,50570,50442,50590,50040,50476,50268,50595,48708,48547,48196,48375,47915,46462,46132,46308,46532,46817,46824,46263,45992,46404,46995,48102,48719,47912,48430,50141,50608,51005,51857,52513,52406,53634,55165,57294,58026,56701,58706,60103,61153,62395,63850,64534,65765,66954,65741,65474,60687,59227,59373,59995,59532,59696,59507,60210,58782,59372,58827,60481,59508,56565,56201,56193,56431,56316,55316,54795,53310,51848,50618,52026,50120,46825,46374,45441,45392,45032,44302,42880,42101,41886,41415,43228,41633,39375,38603,37847,36881,36700,36477,35684,35896,37109,37612,39570,39518,37970,38343,37966,38942,39304,39438,38999,38110,40024,41050,42239,42313,41159,42067,42515,43554,45018,45797,46749,47291,48800,50566,54884,54002,51813,52751,54461,55364,56900,57795)
> 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] 128
> (np <- floor(n / par1))
[1] 32
> 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,] 52347 50590 50595 48375 46308 46263 48102 50141 52513 57294 60103 64534
[2,] 52407 50040 48708 47915 46532 45992 48719 50608 52406 58026 61153 65765
[3,] 50570 50476 48547 46462 46817 46404 47912 51005 53634 56701 62395 66954
[4,] 50442 50268 48196 46132 46824 46995 48430 51857 55165 58706 63850 65741
     [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
[1,] 65474 59995 60210 60481 56193 54795 52026 45441 42880 43228 37847 35684
[2,] 60687 59532 58782 59508 56431 53310 50120 45392 42101 41633 36881 35896
[3,] 59227 59696 59372 56565 56316 51848 46825 45032 41886 39375 36700 37109
[4,] 59373 59507 58827 56201 55316 50618 46374 44302 41415 38603 36477 37612
     [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32]
[1,] 39570 37966 38999 42239 42515 46749 54884 54461
[2,] 39518 38942 38110 42313 43554 47291 54002 55364
[3,] 37970 39304 40024 41159 45018 48800 51813 56900
[4,] 38343 39438 41050 42067 45797 50566 52751 57795
> 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] 51441.50 50343.50 49011.50 47221.00 46620.25 46413.50 48290.75 50902.75
 [9] 53429.50 57681.75 61875.25 65748.50 61190.25 59682.50 59297.75 58188.75
[17] 56064.00 52642.75 48836.25 45041.75 42070.50 40709.75 36976.25 36575.25
[25] 38850.25 38912.50 39545.75 41944.50 44221.00 48351.50 53362.50 56130.00
> arr.sd
 [1] 1081.7629  242.3022 1077.0925 1091.6889  248.6716  423.6921  356.7757
 [8]  727.5962 1283.3946  871.7448 1615.7860  988.0231 2930.3312  224.5655
[15]  664.6595 2127.7958  508.0479 1808.1890 2703.7209  525.8012  610.9940
[22] 2114.5470  603.5569  933.7107  815.6945  664.8697 1271.7186  533.7100
[29] 1469.0484 1712.4864 1353.8593 1498.6040
> arr.range
 [1] 1965  550 2399 2243  516 1003  807 1716 2759 2005 3747 2420 6247  488 1428
[16] 4280 1115 4177 5652 1139 1465 4625 1370 1928 1600 1472 2940 1154 3282 3817
[31] 3071 3334
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  103.48738      0.02001  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      0.01225        0.62783  

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

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

Coefficients:
(Intercept)     arr.mean  
  147.60433      0.04535  

> postscript(file="/var/yougetitorg/rcomp/tmp/1viqu1295183430.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/yougetitorg/rcomp/tmp/2m2hc1295183430.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/yougetitorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/yougetitorg/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/yougetitorg/rcomp/tmp/3kb7h1295183430.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/yougetitorg/rcomp/tmp/45tpu1295183430.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/yougetitorg/rcomp/tmp/5hnnb1295183430.tab") 
> 
> try(system("convert tmp/1viqu1295183430.ps tmp/1viqu1295183430.png",intern=TRUE))
character(0)
> try(system("convert tmp/2m2hc1295183430.ps tmp/2m2hc1295183430.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.720   0.440   0.928