R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(9.026,9.787,9.536,9.490,9.736,9.694,9.647,9.753,10.070,10.137,9.984,9.732,9.103,9.155,9.308,9.394,9.948,10.177,10.002,9.728,10.002,10.063,10.018,9.960,10.236,10.893,10.756,10.940,10.997,10.827,10.166,10.186,10.457,10.368,10.244,10.511,10.812,10.738,10.171,9.721,9.897,9.828,9.924,10.371,10.846,10.413,10.709,10.662,10.570,10.297,10.635,10.872,10.296,10.383,10.431,10.574,10.653,10.805,10.872,10.625,10.407,10.463,10.556,10.646,10.702,11.353,11.346,11.451,11.964,12.574,13.031,13.812,14.544,14.931,14.886,16.005,17.064,15.168,16.050,15.839,15.137,14.954,15.648,15.305,15.579,16.348,15.928,16.171,15.937,15.713,15.594,15.683,16.438,17.032,17.696,17.745,19.394,20.148,20.108,18.584,18.441,18.391,19.178,18.079,18.483,19.644,19.195,19.650,20.830,23.595,22.937,21.814,21.928,21.777,21.383,21.467,22.052,22.680,24.320,24.977,25.204,25.739,26.434,27.525,30.695,32.436,30.160,30.236,31.293,31.077,32.226)
> 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] 131
> (np <- floor(n / par1))
[1] 10
> 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,]  9.026  9.103 10.236 10.812 10.570 10.407 14.544 15.579 19.394 20.830
 [2,]  9.787  9.155 10.893 10.738 10.297 10.463 14.931 16.348 20.148 23.595
 [3,]  9.536  9.308 10.756 10.171 10.635 10.556 14.886 15.928 20.108 22.937
 [4,]  9.490  9.394 10.940  9.721 10.872 10.646 16.005 16.171 18.584 21.814
 [5,]  9.736  9.948 10.997  9.897 10.296 10.702 17.064 15.937 18.441 21.928
 [6,]  9.694 10.177 10.827  9.828 10.383 11.353 15.168 15.713 18.391 21.777
 [7,]  9.647 10.002 10.166  9.924 10.431 11.346 16.050 15.594 19.178 21.383
 [8,]  9.753  9.728 10.186 10.371 10.574 11.451 15.839 15.683 18.079 21.467
 [9,] 10.070 10.002 10.457 10.846 10.653 11.964 15.137 16.438 18.483 22.052
[10,] 10.137 10.063 10.368 10.413 10.805 12.574 14.954 17.032 19.644 22.680
[11,]  9.984 10.018 10.244 10.709 10.872 13.031 15.648 17.696 19.195 24.320
[12,]  9.732  9.960 10.511 10.662 10.625 13.812 15.305 17.745 19.650 24.977
> 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]  9.716000  9.738167 10.548417 10.341000 10.584417 11.525417 15.460917
 [8] 16.322000 19.107917 22.480000
> arr.sd
 [1] 0.2932991 0.3879986 0.3168267 0.4184949 0.2029753 1.1129537 0.6951091
 [8] 0.7756835 0.7032357 1.2609669
> arr.range
 [1] 1.111 1.074 0.831 1.125 0.576 3.405 2.520 2.166 2.069 4.147
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.17533      0.05832  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -4.405          1.468  

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

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

Coefficients:
(Intercept)     arr.mean  
    -0.7398       0.1945  

> postscript(file="/var/www/rcomp/tmp/1hcas1292966923.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/rcomp/tmp/2hcas1292966923.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/32dqy1292966923.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4y5ah1292966924.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/rcomp/tmp/5j6q41292966924.tab") 
> 
> try(system("convert tmp/1hcas1292966923.ps tmp/1hcas1292966923.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hcas1292966923.ps tmp/2hcas1292966923.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.550   0.450   0.977