R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(90.6,91,90.7,91.3,91.5,91.2,91.2,91.5,92,91.7,91.7,92,91.5,91.7,92.1,92,91.8,91.4,91.3,91.5,92.3,92.7,92.1,92.3,92.3,92.5,92.3,92.7,93.4,93.1,93.8,94.6,94.5,94.4,94.2,93.5,93.1,93.1,93,93.5,93.5,92.9,92.8,92.3,91.8,91.3,90.6,90,89.7,89.6,90,90.9,91.2,91.3,92.2,92.7,93,93.2,94.1,95.1,95.1,96.6,97.8,97.7,99,99.3,100.4,101.2,103.1,104.3,103.7,102,100.5,101,101.3,101.3,101.3,100.8,100.7,100.6,101.1,100.7,100.6,100.5,101.5,101.5,101.5,102.1,102.1,102.2,102.4,102.5,102.6,102.8,102.8,103.1,102.5,102.9,103.6,104,103.5,103.1,102.4,102.2,102.4,102.6,102.8,102.8,103.6,104.7,105.5,106.6,107.2,107.5,108.3,108.7,108.8,109.8,109.5,109.2,110.6,110.1,109.9,109.7,109.4,109.4,109.4,109.5,109.5,109.9,110,110.8,112.4,112.8,113.7,114.5,114.8,115.6,115.8,115.8,116.3,116.3,116.8,116.7,116.8,117,117.2,117.1,117.3,117.4,117.7,117.9,118.8,119.9,122.4,123.5,125.6,127.4,128.9,129.5,130.8,132.7,134,132.9,133.1,131.7,128.8,125.1)
> 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] 168
> (np <- floor(n / par1))
[1] 14
> 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] [,13]
 [1,] 90.6 91.5 92.3 93.1 89.7  95.1 100.5 101.5 102.5 103.6 110.6 112.4 116.8
 [2,] 91.0 91.7 92.5 93.1 89.6  96.6 101.0 101.5 102.9 104.7 110.1 112.8 117.0
 [3,] 90.7 92.1 92.3 93.0 90.0  97.8 101.3 101.5 103.6 105.5 109.9 113.7 117.2
 [4,] 91.3 92.0 92.7 93.5 90.9  97.7 101.3 102.1 104.0 106.6 109.7 114.5 117.1
 [5,] 91.5 91.8 93.4 93.5 91.2  99.0 101.3 102.1 103.5 107.2 109.4 114.8 117.3
 [6,] 91.2 91.4 93.1 92.9 91.3  99.3 100.8 102.2 103.1 107.5 109.4 115.6 117.4
 [7,] 91.2 91.3 93.8 92.8 92.2 100.4 100.7 102.4 102.4 108.3 109.4 115.8 117.7
 [8,] 91.5 91.5 94.6 92.3 92.7 101.2 100.6 102.5 102.2 108.7 109.5 115.8 117.9
 [9,] 92.0 92.3 94.5 91.8 93.0 103.1 101.1 102.6 102.4 108.8 109.5 116.3 118.8
[10,] 91.7 92.7 94.4 91.3 93.2 104.3 100.7 102.8 102.6 109.8 109.9 116.3 119.9
[11,] 91.7 92.1 94.2 90.6 94.1 103.7 100.6 102.8 102.8 109.5 110.0 116.8 122.4
[12,] 92.0 92.3 93.5 90.0 95.1 102.0 100.5 103.1 102.8 109.2 110.8 116.7 123.5
      [,14]
 [1,] 125.6
 [2,] 127.4
 [3,] 128.9
 [4,] 129.5
 [5,] 130.8
 [6,] 132.7
 [7,] 134.0
 [8,] 132.9
 [9,] 133.1
[10,] 131.7
[11,] 128.8
[12,] 125.1
> 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]  91.36667  91.89167  93.44167  92.32500  91.91667 100.01667 100.86667
 [8] 102.25833 102.90000 107.45000 109.85000 115.12500 118.58333 130.04167
> arr.sd
 [1] 0.4559373 0.4294994 0.8659817 1.1553236 1.7657516 2.9322140 0.3171846
 [8] 0.5451577 0.5526794 1.9970433 0.4700097 1.4936989 2.2282620 2.9825122
> arr.range
 [1] 1.4 1.4 2.3 3.5 5.5 9.2 0.8 1.6 1.8 6.2 1.4 4.4 6.7 8.9
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -3.19507      0.04345  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -15.314          3.304  

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

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

Coefficients:
(Intercept)     arr.mean  
    -9.3368       0.1283  

> postscript(file="/var/www/html/rcomp/tmp/1fpe21259919015.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/html/rcomp/tmp/2wy5q1259919015.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/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/html/rcomp/tmp/359wd1259919015.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4j12z1259919015.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/html/rcomp/tmp/5uopv1259919015.tab") 
> system("convert tmp/1fpe21259919015.ps tmp/1fpe21259919015.png")
> system("convert tmp/2wy5q1259919015.ps tmp/2wy5q1259919015.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.500   0.271   1.148