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(162.9,164.7,165,167.2,168.6,169.5,169.8,171.9,172,173.7,173.9,175.9,175.6,176.1,176.3,179.4,179.7,179.9,180.4,182.5,183.6,183.9,184.5,187.6,188,188.5,188.6,191.9,193.5,194.9,194.9,196.2,196.2,198,198.6,201.3,203.5,204.1,204.8,206.5,207.8,208.6,209.7,210,211.7,212.4,213.7,214.8,216.4,217.5,218.6,220.4,221.8,222.5,223.4,225.5,226.5,227.8,228.5,229.1,229.9,230.8,231.9,236,237.5,239.1,240.5,241.4,243.2,243.6,244.3,244.5,245.1,245.8,246.7,247.7,248.5)
> 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] 77
> (np <- floor(n / par1))
[1] 19
> 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,] 162.9 168.6 172.0 175.6 179.7 183.6 188.0 193.5 196.2 203.5 207.8 211.7
[2,] 164.7 169.5 173.7 176.1 179.9 183.9 188.5 194.9 198.0 204.1 208.6 212.4
[3,] 165.0 169.8 173.9 176.3 180.4 184.5 188.6 194.9 198.6 204.8 209.7 213.7
[4,] 167.2 171.9 175.9 179.4 182.5 187.6 191.9 196.2 201.3 206.5 210.0 214.8
     [,13] [,14] [,15] [,16] [,17] [,18] [,19]
[1,] 216.4 221.8 226.5 229.9 237.5 243.2 245.1
[2,] 217.5 222.5 227.8 230.8 239.1 243.6 245.8
[3,] 218.6 223.4 228.5 231.9 240.5 244.3 246.7
[4,] 220.4 225.5 229.1 236.0 241.4 244.5 247.7
> 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] 164.950 169.950 173.875 176.850 180.625 184.900 189.250 194.875 198.525
[10] 204.725 209.025 213.150 218.225 223.300 227.975 232.150 239.625 243.900
[19] 246.325
> arr.sd
 [1] 1.7635192 1.3964240 1.5966110 1.7253019 1.2841988 1.8384776 1.7860571
 [8] 1.1026483 2.1124630 1.2971122 1.0144785 1.3771952 1.7056279 1.6062378
[15] 1.1176612 2.6938201 1.7036725 0.6055301 1.1265730
> arr.range
 [1] 4.3 3.3 3.9 3.8 2.8 4.0 3.9 2.7 5.1 3.0 2.2 3.1 4.0 3.7 2.6 6.1 3.9 1.3 2.6
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   2.186807    -0.003262  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       4.2383        -0.7276  

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

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

Coefficients:
(Intercept)     arr.mean  
    5.23697     -0.00853  

> postscript(file="/var/wessaorg/rcomp/tmp/1l6jm1323176194.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/277vb1323176194.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/3uoqo1323176194.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4i3lx1323176194.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5jl6r1323176194.tab") 
> 
> try(system("convert tmp/1l6jm1323176194.ps tmp/1l6jm1323176194.png",intern=TRUE))
character(0)
> try(system("convert tmp/277vb1323176194.ps tmp/277vb1323176194.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.607   0.108   0.724