R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(1.0137,0.9834,0.9643,0.947,0.906,0.9492,0.9397,0.9041,0.8721,0.8552,0.8564,0.8973,0.9383,0.9217,0.9095,0.892,0.8742,0.8532,0.8607,0.9005,0.9111,0.9059,0.8883,0.8924,0.8833,0.87,0.8758,0.8858,0.917,0.9554,0.9922,0.9778,0.9808,0.9811,1.0014,1.0183,1.0622,1.0773,1.0807,1.0848,1.1582,1.1663,1.1372,1.1139,1.1222,1.1692,1.1702,1.2286,1.2613,1.2646,1.2262,1.1985,1.2007,1.2138,1.2266,1.2176,1.2218,1.249,1.2991,1.3408,1.3119,1.3014,1.3201,1.2938,1.2694,1.2165,1.2037,1.2292,1.2256,1.2015,1.1786,1.1856,1.2103,1.1938,1.202,1.2271,1.277,1.265,1.2684,1.2811,1.2727,1.2611,1.2881,1.3213,1.2999,1.3074,1.3242,1.3516,1.3511,1.3419,1.3716,1.3622,1.3896,1.4227,1.4684,1.457,1.4718)
> 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] 97
> (np <- floor(n / par1))
[1] 24
> 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,] 1.0137 0.9060 0.8721 0.9383 0.8742 0.9111 0.8833 0.9170 0.9808 1.0622
[2,] 0.9834 0.9492 0.8552 0.9217 0.8532 0.9059 0.8700 0.9554 0.9811 1.0773
[3,] 0.9643 0.9397 0.8564 0.9095 0.8607 0.8883 0.8758 0.9922 1.0014 1.0807
[4,] 0.9470 0.9041 0.8973 0.8920 0.9005 0.8924 0.8858 0.9778 1.0183 1.0848
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
[1,] 1.1582 1.1222 1.2613 1.2007 1.2218 1.3119 1.2694 1.2256 1.2103 1.2770
[2,] 1.1663 1.1692 1.2646 1.2138 1.2490 1.3014 1.2165 1.2015 1.1938 1.2650
[3,] 1.1372 1.1702 1.2262 1.2266 1.2991 1.3201 1.2037 1.1786 1.2020 1.2684
[4,] 1.1139 1.2286 1.1985 1.2176 1.3408 1.2938 1.2292 1.1856 1.2271 1.2811
      [,21]  [,22]  [,23]  [,24]
[1,] 1.2727 1.2999 1.3511 1.3896
[2,] 1.2611 1.3074 1.3419 1.4227
[3,] 1.2881 1.3242 1.3716 1.4684
[4,] 1.3213 1.3516 1.3622 1.4570
> 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] 0.977100 0.924750 0.870250 0.915375 0.872150 0.899425 0.878725 0.960600
 [9] 0.995400 1.076250 1.143900 1.172550 1.237650 1.214675 1.277675 1.306800
[17] 1.229700 1.197825 1.208300 1.272875 1.285800 1.320775 1.356700 1.434425
> arr.sd
 [1] 0.028572131 0.023088886 0.019608247 0.019548806 0.020801683 0.010822007
 [7] 0.007203414 0.032773973 0.018056024 0.009855794 0.023460179 0.043564014
[13] 0.031355223 0.010752170 0.052877429 0.011562295 0.028440464 0.020848721
[19] 0.014228844 0.007454473 0.026123042 0.022924278 0.012944239 0.035640275
> arr.range
 [1] 0.0667 0.0451 0.0421 0.0463 0.0473 0.0228 0.0158 0.0752 0.0375 0.0226
[11] 0.0524 0.1064 0.0661 0.0259 0.1190 0.0263 0.0657 0.0470 0.0333 0.0161
[21] 0.0602 0.0517 0.0297 0.0788
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   0.006159     0.014232  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -3.9997         0.5694  

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

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

Coefficients:
(Intercept)     arr.mean  
    0.01123      0.03443  

> postscript(file="/var/www/html/rcomp/tmp/1k65f1228293857.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/238bj1228293857.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/3qof51228293857.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4msbr1228293857.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5ycnq1228293857.tab") 
> 
> system("convert tmp/1k65f1228293857.ps tmp/1k65f1228293857.png")
> system("convert tmp/238bj1228293857.ps tmp/238bj1228293857.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.529   0.295   0.794