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

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(2072.65,2020.13,2032.76,2050.31,2128.98,2122.14,2122.89,2091.95,2002.97,1923.21,1834.44,1819.15,1792.00,1822.40,1900.70,1903.00,1958.80,1820.50,1719.80,1661.10,1664.40,1703.40,1774.90,1795.00,1816.30,1867.40,1900.00,1961.10,2065.70,2073.50,2080.80,2118.00,2099.00,2085.20,1937.70,1749.50,1750.30,1675.60,1697.50,1699.80,1655.90,1636.00,1614.20,1602.30,1548.70,1556.10,1526.90,1509.20,1566.30,1596.00,1654.50,1664.20,1687.70,1691.00,1664.60,1697.50,1685.10,1643.00,1559.60,1560.20,1590.16,1604.93,1661.80,1670.73,1692.40,1688.17,1658.04,1613.46,1595.11,1558.83,1526.65,1475.19)
> 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] 72
> (np <- floor(n / par1))
[1] 6
> 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]
 [1,] 2072.65 1792.0 1816.3 1750.3 1566.3 1590.16
 [2,] 2020.13 1822.4 1867.4 1675.6 1596.0 1604.93
 [3,] 2032.76 1900.7 1900.0 1697.5 1654.5 1661.80
 [4,] 2050.31 1903.0 1961.1 1699.8 1664.2 1670.73
 [5,] 2128.98 1958.8 2065.7 1655.9 1687.7 1692.40
 [6,] 2122.14 1820.5 2073.5 1636.0 1691.0 1688.17
 [7,] 2122.89 1719.8 2080.8 1614.2 1664.6 1658.04
 [8,] 2091.95 1661.1 2118.0 1602.3 1697.5 1613.46
 [9,] 2002.97 1664.4 2099.0 1548.7 1685.1 1595.11
[10,] 1923.21 1703.4 2085.2 1556.1 1643.0 1558.83
[11,] 1834.44 1774.9 1937.7 1526.9 1559.6 1526.65
[12,] 1819.15 1795.0 1749.5 1509.2 1560.2 1475.19
> 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] 2018.465 1793.000 1979.517 1622.708 1639.142 1611.289
> arr.sd
[1] 107.16564  95.56726 124.92537  76.49041  53.78209  67.38756
> arr.range
[1] 309.83 297.70 368.50 241.10 137.90 217.21
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  -144.0976       0.1303  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -15.785          2.703  

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

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

Coefficients:
(Intercept)     arr.mean  
  -380.9413       0.3618  

> postscript(file="/var/www/html/rcomp/tmp/1mp3z1262173437.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/2iszv1262173437.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/3vaq31262173437.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4tb8o1262173437.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5w3oi1262173437.tab") 
> 
> try(system("convert tmp/1mp3z1262173437.ps tmp/1mp3z1262173437.png",intern=TRUE))
character(0)
> try(system("convert tmp/2iszv1262173437.ps tmp/2iszv1262173437.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.499   0.294   0.671