R version 2.6.2 (2008-02-08)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(1.1591,1.1203,1.0886,1.0701,1.0630,1.0377,1.0370,1.0606,1.0497,1.0706,1.0328,1.0110,1.0131,0.9834,0.9643,0.9449,0.9059,0.9505,0.9386,0.9045,0.8695,0.8525,0.8552,0.8983,0.9376,0.9205,0.9083,0.8925,0.8753,0.8530,0.8615,0.9014,0.9114,0.9050,0.8883,0.8912,0.8832,0.8706,0.8766,0.8860,0.9170,0.9561,0.9935,0.9781,0.9806,0.9812,1.0013,1.0194,1.0622,1.0785,1.0805,1.0862,1.1556,1.1674,1.1365,1.1155,1.1266,1.1714,1.1710,1.2298,1.2638,1.2640,1.2261,1.1989,1.2000,1.2146,1.2266,1.2191,1.2224,1.2507,1.2997,1.3406)
> 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] 72
> (np <- floor(n / par1))
[1] 18
> 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,] 1.1591 1.0630 1.0497 1.0131 0.9059 0.8695 0.9376 0.8753 0.9114 0.8832
[2,] 1.1203 1.0377 1.0706 0.9834 0.9505 0.8525 0.9205 0.8530 0.9050 0.8706
[3,] 1.0886 1.0370 1.0328 0.9643 0.9386 0.8552 0.9083 0.8615 0.8883 0.8766
[4,] 1.0701 1.0606 1.0110 0.9449 0.9045 0.8983 0.8925 0.9014 0.8912 0.8860
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]
[1,] 0.9170 0.9806 1.0622 1.1556 1.1266 1.2638 1.2000 1.2224
[2,] 0.9561 0.9812 1.0785 1.1674 1.1714 1.2640 1.2146 1.2507
[3,] 0.9935 1.0013 1.0805 1.1365 1.1710 1.2261 1.2266 1.2997
[4,] 0.9781 1.0194 1.0862 1.1155 1.2298 1.1989 1.2191 1.3406
> 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] 1.109525 1.049575 1.041025 0.976425 0.924875 0.868875 0.914725 0.872800
 [9] 0.898975 0.879100 0.961175 0.995625 1.076850 1.143750 1.174700 1.238200
[17] 1.215075 1.278350
> arr.sd
 [1] 0.039012680 0.014153062 0.025292209 0.029066289 0.023239388 0.020987040
 [7] 0.019077452 0.021165538 0.011031583 0.006902174 0.033209173 0.018540833
[13] 0.010297087 0.022733016 0.042324934 0.031685433 0.011202790 0.052363505
> arr.range
 [1] 0.0890 0.0260 0.0596 0.0682 0.0460 0.0458 0.0451 0.0484 0.0231 0.0154
[11] 0.0765 0.0388 0.0240 0.0519 0.1032 0.0651 0.0266 0.1182
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.02438      0.04678  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -3.905          1.787  

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

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

Coefficients:
(Intercept)     arr.mean  
   -0.05817      0.10838  

> postscript(file="/var/www/html/freestat/rcomp/tmp/1gpgp1211021966.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/freestat/rcomp/tmp/22a1o1211021966.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/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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/freestat/rcomp/tmp/3u2la1211021966.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/4302w1211021966.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/freestat/rcomp/tmp/58skw1211021966.tab") 
> 
> system("convert tmp/1gpgp1211021966.ps tmp/1gpgp1211021966.png")
> system("convert tmp/22a1o1211021966.ps tmp/22a1o1211021966.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.989   0.394   1.051