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(98.6,100.1,98.8,98.3,102.8,103.6,105.2,100.1,98.2,98.4,97.4,98.4,100.3,101.1,104.1,107.3,110.1,112.6,114.3,115.3,109.9,108.2,103.2,101.8,105.6,108.2,109.8,114.6,117.2,116.5,116.1,112.1,106.8,106.9,104.5,103,105.9,107.7,107.1,112.5,114.5,114.6,113.1,112.8,111.9,112,112.4,110,112.3,109.6,111.9,110.8,110.4,110.8,114,108.4,110.5,105.1,102.3,104.3,103.4,102.4,104.5,107.3,110.1,111.8,111.8,105.7,106,106.4,107.1,111.5,109.6,109.9,109.3,111.4,112.9,115.5,118.4,116.2,113.3,113.8,114.1,117.1,115.5,115.2,114.2,115.3,118.8,118,118.1,111.8,112,114.3,115,118.5,117.6,119.1,120.6,123.6,122.7,123.8,123.1,124.5,120.7,118.7,119,122.3,118.6,118.1,118.2,120.8,119.7,119.7,117.1,114.5,116.5,116.4,114.9,115.5)
> par1 = '12'
> #'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] 10
> 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,]  98.6 100.3 105.6 105.9 112.3 103.4 109.6 115.5 117.6 118.6
 [2,] 100.1 101.1 108.2 107.7 109.6 102.4 109.9 115.2 119.1 118.1
 [3,]  98.8 104.1 109.8 107.1 111.9 104.5 109.3 114.2 120.6 118.2
 [4,]  98.3 107.3 114.6 112.5 110.8 107.3 111.4 115.3 123.6 120.8
 [5,] 102.8 110.1 117.2 114.5 110.4 110.1 112.9 118.8 122.7 119.7
 [6,] 103.6 112.6 116.5 114.6 110.8 111.8 115.5 118.0 123.8 119.7
 [7,] 105.2 114.3 116.1 113.1 114.0 111.8 118.4 118.1 123.1 117.1
 [8,] 100.1 115.3 112.1 112.8 108.4 105.7 116.2 111.8 124.5 114.5
 [9,]  98.2 109.9 106.8 111.9 110.5 106.0 113.3 112.0 120.7 116.5
[10,]  98.4 108.2 106.9 112.0 105.1 106.4 113.8 114.3 118.7 116.4
[11,]  97.4 103.2 104.5 112.4 102.3 107.1 114.1 115.0 119.0 114.9
[12,]  98.4 101.8 103.0 110.0 104.3 111.5 117.1 118.5 122.3 115.5
> 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]  99.99167 107.35000 110.10833 111.20833 109.20000 107.33333 113.45833
 [8] 115.55833 121.30833 117.50000
> arr.sd
 [1] 2.509422 5.232851 5.031439 2.883640 3.534505 3.277009 3.004681 2.380015
 [9] 2.323969 2.017199
> arr.range
 [1]  7.8 15.0 14.2  8.7 11.7  9.4  9.1  7.0  6.9  6.3
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   11.19635     -0.07167  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       12.539         -2.424  

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

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

Coefficients:
(Intercept)     arr.mean  
    33.3479      -0.2133  

> postscript(file="/var/wessaorg/rcomp/tmp/1htg01323175585.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/20kb01323175585.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/3jh4b1323175585.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/46emo1323175585.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5ymac1323175585.tab") 
> 
> try(system("convert tmp/1htg01323175585.ps tmp/1htg01323175585.png",intern=TRUE))
character(0)
> try(system("convert tmp/20kb01323175585.ps tmp/20kb01323175585.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.631   0.107   0.815