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(5221.3,5115.9,5107.4,5202.1,5307.5,5266.1,5329.8,5263.4,5177.1,5204.9,5185.2,5189.8,5253.8,5372.3,5478.4,5590.5,5699.8,5797.9,5854.3,5902.4,5956.9,6007.8,6101.7,6148.6,6207.4,6232,6291.7,6323.4,6365,6435,6493.4,6606.8,6639.1,6723.5,6759.4,6848.6,6918.1,6963.5,7013.1,7030.9,7112.1,7130.3,7130.8,7076.9,7040.8,7086.5,7120.7,7154.1,7228.2,7297.9,7369.5,7450.7,7459.7,7497.5,7536,7637.4,7715.1,7815.7,7859.5,7951.6,7973.7,7988,8053.1,8112,8169.2,8303.1,8372.7,8470.6,8536.1,8665.8,8773.7,8838.4,8936.2,8995.3,9098.9,9237.1,9315.5,9392.6,9502.2,9671.1,9695.6,9847.9,9836.6,9887.7,9875.6,9905.9,9871.1,9910,9977.3,10031.6,10090.7,10095.8,10126,10212.7,10398.7,10467,10543.6,10634.2,10728.7,10796.4,10875.8,10946.1,11050,11086.1,11217.3,11291.7,11314.1,11356.4,11357.8,11491.4,11625.7,11620.7)
> 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] 112
> (np <- floor(n / par1))
[1] 28
> 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]
[1,] 5221.3 5307.5 5177.1 5253.8 5699.8 5956.9 6207.4 6365.0 6639.1 6918.1
[2,] 5115.9 5266.1 5204.9 5372.3 5797.9 6007.8 6232.0 6435.0 6723.5 6963.5
[3,] 5107.4 5329.8 5185.2 5478.4 5854.3 6101.7 6291.7 6493.4 6759.4 7013.1
[4,] 5202.1 5263.4 5189.8 5590.5 5902.4 6148.6 6323.4 6606.8 6848.6 7030.9
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
[1,] 7112.1 7040.8 7228.2 7459.7 7715.1 7973.7 8169.2 8536.1 8936.2 9315.5
[2,] 7130.3 7086.5 7297.9 7497.5 7815.7 7988.0 8303.1 8665.8 8995.3 9392.6
[3,] 7130.8 7120.7 7369.5 7536.0 7859.5 8053.1 8372.7 8773.7 9098.9 9502.2
[4,] 7076.9 7154.1 7450.7 7637.4 7951.6 8112.0 8470.6 8838.4 9237.1 9671.1
      [,21]  [,22]   [,23]   [,24]   [,25]   [,26]   [,27]   [,28]
[1,] 9695.6 9875.6  9977.3 10126.0 10543.6 10875.8 11217.3 11357.8
[2,] 9847.9 9905.9 10031.6 10212.7 10634.2 10946.1 11291.7 11491.4
[3,] 9836.6 9871.1 10090.7 10398.7 10728.7 11050.0 11314.1 11625.7
[4,] 9887.7 9910.0 10095.8 10467.0 10796.4 11086.1 11356.4 11620.7
> 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]  5161.675  5291.700  5189.250  5423.750  5813.600  6053.750  6263.625
 [8]  6475.050  6742.650  6981.400  7112.525  7100.525  7336.575  7532.650
[15]  7835.475  8031.700  8328.900  8703.500  9066.875  9470.350  9816.950
[22]  9890.650 10048.850 10301.100 10675.725 10989.500 11294.875 11523.900
> arr.sd
 [1]  58.39648  32.44226  11.67975 144.13222  87.06101  87.15322  53.29993
 [8] 102.32268  86.78573  50.93277  25.29326  48.44615  95.48031  76.46570
[15]  98.22323  63.71745 126.71104 132.37585 131.91043 154.20611  83.81609
[22]  20.13033  55.89481 158.66436 110.37836  96.26882  58.26059 126.98942
> arr.range
 [1] 113.9  66.4  27.8 336.7 202.6 191.7 116.0 241.8 209.5 112.8  53.9 113.3
[13] 222.5 177.7 236.5 138.3 301.4 302.3 300.9 355.6 192.1  38.9 118.5 341.0
[25] 252.8 210.3 139.1 267.9
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  29.471134     0.006916  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -3.4949         0.8685  

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

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

Coefficients:
(Intercept)     arr.mean  
   74.07707      0.01474  

> postscript(file="/var/www/rcomp/tmp/174js1274800247.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/rcomp/tmp/274js1274800247.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/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/3tn0g1274800247.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4eny41274800247.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/506fs1274800247.tab") 
> 
> try(system("convert tmp/174js1274800247.ps tmp/174js1274800247.png",intern=TRUE))
character(0)
> try(system("convert tmp/274js1274800247.ps tmp/274js1274800247.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   0.65    0.52    1.02