R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.

  Natural language support but running in an English locale

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(14.458,13.594,17.814,20.235,21.811,21.439,21.393,19.831,20.468,21.080,21.600,17.390,17.848,19.592,21.092,20.899,25.890,24.965,22.225,20.977,22.897,22.785,22.769,19.637,20.203,20.450,23.083,21.738,26.766,25.280,22.574,22.729,21.378,22.902,24.989,21.116,15.169,15.846,20.927,18.273,22.538,15.596,14.034,11.366,14.861,15.149,13.577,13.026,13.190,13.196,15.826,14.733,16.307,15.703,14.589,12.043,15.057,14.053,12.698,10.888,10.045,11.549,13.767,12.434,13.116,14.211,12.266,12.602,15.714,13.742,12.745,10.491,10.057,10.900,11.771,11.992,11.933,14.504,11.727,11.477,13.578,11.555,11.846,11.397,10.066,10.269,14.279,13.870,13.695,14.420,11.424,9.704,12.464,14.301,13.464,9.893,11.572,12.380,16.692,16.052,16.459,14.761,13.654,13.480,18.068,16.560,14.530,10.650,11.651,13.735,13.360,17.818,20.613,16.231,13.862,12.004,17.734,15.034,12.609,12.320,10.833,11.350,13.648,14.890,16.325,18.045,15.616,11.926,16.855,15.083,12.520,12.355)
> 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] 132
> (np <- floor(n / par1))
[1] 11
> 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,] 14.458 17.848 20.203 15.169 13.190 10.045 10.057 10.066 11.572 11.651
 [2,] 13.594 19.592 20.450 15.846 13.196 11.549 10.900 10.269 12.380 13.735
 [3,] 17.814 21.092 23.083 20.927 15.826 13.767 11.771 14.279 16.692 13.360
 [4,] 20.235 20.899 21.738 18.273 14.733 12.434 11.992 13.870 16.052 17.818
 [5,] 21.811 25.890 26.766 22.538 16.307 13.116 11.933 13.695 16.459 20.613
 [6,] 21.439 24.965 25.280 15.596 15.703 14.211 14.504 14.420 14.761 16.231
 [7,] 21.393 22.225 22.574 14.034 14.589 12.266 11.727 11.424 13.654 13.862
 [8,] 19.831 20.977 22.729 11.366 12.043 12.602 11.477  9.704 13.480 12.004
 [9,] 20.468 22.897 21.378 14.861 15.057 15.714 13.578 12.464 18.068 17.734
[10,] 21.080 22.785 22.902 15.149 14.053 13.742 11.555 14.301 16.560 15.034
[11,] 21.600 22.769 24.989 13.577 12.698 12.745 11.846 13.464 14.530 12.609
[12,] 17.390 19.637 21.116 13.026 10.888 10.491 11.397  9.893 10.650 12.320
       [,11]
 [1,] 10.833
 [2,] 11.350
 [3,] 13.648
 [4,] 14.890
 [5,] 16.325
 [6,] 18.045
 [7,] 15.616
 [8,] 11.926
 [9,] 16.855
[10,] 15.083
[11,] 12.520
[12,] 12.355
> 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] 19.25942 21.79800 22.76733 15.86350 14.02358 12.72350 11.89475 12.32075
 [9] 14.57150 14.74758 14.12050
> arr.sd
 [1] 2.829710 2.280371 2.023898 3.232188 1.653273 1.574866 1.152184 1.921608
 [9] 2.289886 2.801778 2.348986
> arr.range
 [1]  8.217  8.042  6.563 11.172  5.419  5.669  4.447  4.716  7.418  8.962
[11]  7.212
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    1.24785      0.05964  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.0045         0.6394  

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

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

Coefficients:
(Intercept)     arr.mean  
     3.7810       0.2082  

> postscript(file="/var/www/html/freestat/rcomp/tmp/1o0cz1292697618.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/freestat/rcomp/tmp/2o0cz1292697618.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/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/39jsm1292697618.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/4vj8s1292697618.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5rbo11292697618.tab") 
> 
> try(system("convert tmp/1o0cz1292697618.ps tmp/1o0cz1292697618.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o0cz1292697618.ps tmp/2o0cz1292697618.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.828   0.426   0.959