R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(58109,57087,56064,54019,74712,73689,58109,47763,48785,48785,49808,51964,45718,39462,34339,34339,54019,56064,40484,22859,32183,32183,39462,43663,42640,32183,37417,35362,52987,48785,32183,19782,31160,34339,37417,41507,33205,26038,29116,30138,57087,57087,41507,39462,45718,42640,50942,61288,63343,48785,44685,40484,68567,70622,65388,70622,69589,61288,70622,80968,85169,72667,64365,70622,97570,105872,103827,107916,106894,96548,114173,118374,124519,105872,98593,106894,126675,144300,140099,140099,142154,134976,153634,153634,150455,132820,135999,138054,151579,169204,156701,162958,157724,154656,178538,173304,166025,155679,166025,171259,177505,185806,177505,182628,176381,175359,201285,203441,195140,180583,192984,198208,204464,213788,204464,211743,208564,197185,221066,221066)
> 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]
[1,] 58109 74712 48785 45718 54019 32183 42640 52987 31160 33205 57087 45718
[2,] 57087 73689 48785 39462 56064 32183 32183 48785 34339 26038 57087 42640
[3,] 56064 58109 49808 34339 40484 39462 37417 32183 37417 29116 41507 50942
[4,] 54019 47763 51964 34339 22859 43663 35362 19782 41507 30138 39462 61288
     [,13] [,14] [,15] [,16]  [,17]  [,18]  [,19]  [,20]  [,21]  [,22]  [,23]
[1,] 63343 68567 69589 85169  97570 106894 124519 126675 142154 150455 151579
[2,] 48785 70622 61288 72667 105872  96548 105872 144300 134976 132820 169204
[3,] 44685 65388 70622 64365 103827 114173  98593 140099 153634 135999 156701
[4,] 40484 70622 80968 70622 107916 118374 106894 140099 153634 138054 162958
      [,24]  [,25]  [,26]  [,27]  [,28]  [,29]  [,30]
[1,] 157724 166025 177505 176381 195140 204464 208564
[2,] 154656 155679 185806 175359 180583 213788 197185
[3,] 178538 166025 177505 201285 192984 204464 221066
[4,] 173304 171259 182628 203441 198208 211743 221066
> 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]  56319.75  63568.25  49835.50  38464.50  43356.50  36872.75  36900.50
 [8]  38434.25  36105.75  29624.25  48785.75  50147.00  49324.25  68799.75
[15]  70616.75  73205.75 103796.25 108997.25 108969.50 137793.25 146099.50
[22] 139332.00 160110.50 166055.50 164747.00 180861.00 189116.50 191728.75
[29] 208614.75 211970.25
> arr.sd
 [1]  1746.324 12990.023  1498.707  5405.176 15314.135  5680.353  4390.536
 [8] 15339.547  4414.926  2955.516  9621.747  8179.751  9941.308  2472.206
[15]  8067.016  8722.466  4473.932  9558.928 11005.467  7672.163  9180.352
[22]  7721.603  7642.233 11657.845  6529.455  4086.595 15326.725  7733.492
[29]  4865.042 11484.359
> arr.range
 [1]  4090 26949  3179 11379 33205 11480 10457 33205 10347  7167 17625 18648
[13] 22859  5234 19680 20804 10346 21826 25926 17625 18658 17635 17625 23882
[25] 15580  8301 28082 17625  9324 23881
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  6.768e+03    1.085e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       6.0901         0.2410  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.535e+04    1.733e-02  

> postscript(file="/var/www/rcomp/tmp/1973i1313414725.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/www/rcomp/tmp/2udfj1313414725.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/3omdr1313414725.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4lu9s1313414725.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/rcomp/tmp/5qmmw1313414725.tab") 
> 
> try(system("convert tmp/1973i1313414725.ps tmp/1973i1313414725.png",intern=TRUE))
character(0)
> try(system("convert tmp/2udfj1313414725.ps tmp/2udfj1313414725.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.840   0.156   0.970