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(100.00,100.42,100.50,101.14,101.98,102.31,103.27,103.80,103.46,105.06,106.08,106.74,107.35,108.96,109.85,109.81,109.99,111.60,112.74,112.78,113.66,115.37,116.26,116.24,116.73,118.76,119.78,120.23,121.48,124.07,125.82,126.92,128.48,131.44,133.51,134.58,136.68,140.10,142.45,143.91,146.19,149.84,152.31,153.62,155.79,159.89,163.21,165.32,167.68,171.79,175.38,177.81,181.09,186.48,191.07,194.23,197.82,204.41,209.26,212.24,214.88,218.87,219.86,219.75,220.89,224.02,222.27,217.27,213.23,212.44,207.87,199.46,198.19,199.77,200.10,195.76,191.27,195.79,192.7)
> 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] 79
> (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]
[1,] 100.00 101.98 103.46 107.35 109.99 113.66 116.73 121.48 128.48 136.68
[2,] 100.42 102.31 105.06 108.96 111.60 115.37 118.76 124.07 131.44 140.10
[3,] 100.50 103.27 106.08 109.85 112.74 116.26 119.78 125.82 133.51 142.45
[4,] 101.14 103.80 106.74 109.81 112.78 116.24 120.23 126.92 134.58 143.91
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]
[1,] 146.19 155.79 167.68 181.09 197.82 214.88 220.89 213.23 198.19
[2,] 149.84 159.89 171.79 186.48 204.41 218.87 224.02 212.44 199.77
[3,] 152.31 163.21 175.38 191.07 209.26 219.86 222.27 207.87 200.10
[4,] 153.62 165.32 177.81 194.23 212.24 219.75 217.27 199.46 195.76
> 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] 100.5150 102.8400 105.3350 108.9925 111.7775 115.3825 118.8750 124.5725
 [9] 132.0025 140.7850 150.4900 161.0525 173.1650 188.2175 205.9325 218.3400
[17] 221.1125 208.2500 198.4550
> arr.sd
 [1] 0.4708503 0.8420214 1.4283207 1.1693980 1.3112430 1.2209934 1.5566310
 [8] 2.3722756 2.6857944 3.1547900 3.2670986 4.1597947 4.4142987 5.7185976
[15] 6.2978164 2.3488295 2.8640109 6.3183595 1.9806144
> arr.range
 [1]  1.14  1.82  3.28  2.50  2.79  2.60  3.50  5.44  6.10  7.23  7.43  9.53
[13] 10.13 13.14 14.42  4.98  6.75 13.77  4.34
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -1.66162      0.02950  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -8.947          1.959  

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

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

Coefficients:
(Intercept)     arr.mean  
   -3.75722      0.06662  

> postscript(file="/var/www/html/rcomp/tmp/1gz5z1292674772.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/www/html/rcomp/tmp/2gz5z1292674772.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/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/31h351292674772.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/45ikt1292674772.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/58jiz1292674772.tab") 
> 
> try(system("convert tmp/1gz5z1292674772.ps tmp/1gz5z1292674772.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gz5z1292674772.ps tmp/2gz5z1292674772.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.519   0.316   2.960