R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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.

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(5.2100,5.2300,5.2300,5.2300,5.2200,5.2100,5.2300,5.2500,5.2300,5.2300,5.2500,5.2400,5.2600,5.2700,5.2600,5.2900,5.2900,5.2900,5.2900,5.3100,5.3300,5.3400,5.3400,5.3700,5.4100,5.4100,5.3800,5.4400,5.4400,5.4600,5.4600,5.4500,5.4600,5.4600,5.4800,5.4700,5.4800,5.5100,5.5500,5.5800,5.5900,5.6000,5.6000,5.6700,5.7100,5.7000,5.7300,5.7300,5.7200,5.7500,5.7500,5.7700,5.8300,5.8500,5.8700,5.8600,5.8700,5.9300,5.9700,5.9800,5.9900,5.9900,6.0300,6.0600,6.0700,6.0800,6.0800,6.1000,6.1300,6.1400,6.1400,6.1600,6.2000,6.1900,6.3200,6.3200,6.3300,6.3200,6.3300,6.3800,6.4200,6.4600,6.4700,6.4200,6.4800,6.4700,6.4900,6.4800,6.5100,6.5100,6.5200,6.5700,6.5900,6.6200,6.6300,6.6100,6.6400,6.6900,6.6900,6.7500,6.7700,6.8100,6.8100,6.8100,6.8700,6.8600,6.8800,6.8800,6.9200,6.9200,6.9900,7.0200,7.0500,7.0600,7.0600,7.0900,7.1200,7.2300,7.3100,7.4500,7.4900,7.5400,7.5500,7.5800,7.6000,7.6300,7.6400,7.6300,7.6600,7.6400,7.6900,7.7000,7.6800)
> 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] 133
> (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] [,11]
 [1,] 5.21 5.26 5.41 5.48 5.72 5.99 6.20 6.48 6.64  6.92  7.49
 [2,] 5.23 5.27 5.41 5.51 5.75 5.99 6.19 6.47 6.69  6.92  7.54
 [3,] 5.23 5.26 5.38 5.55 5.75 6.03 6.32 6.49 6.69  6.99  7.55
 [4,] 5.23 5.29 5.44 5.58 5.77 6.06 6.32 6.48 6.75  7.02  7.58
 [5,] 5.22 5.29 5.44 5.59 5.83 6.07 6.33 6.51 6.77  7.05  7.60
 [6,] 5.21 5.29 5.46 5.60 5.85 6.08 6.32 6.51 6.81  7.06  7.63
 [7,] 5.23 5.29 5.46 5.60 5.87 6.08 6.33 6.52 6.81  7.06  7.64
 [8,] 5.25 5.31 5.45 5.67 5.86 6.10 6.38 6.57 6.81  7.09  7.63
 [9,] 5.23 5.33 5.46 5.71 5.87 6.13 6.42 6.59 6.87  7.12  7.66
[10,] 5.23 5.34 5.46 5.70 5.93 6.14 6.46 6.62 6.86  7.23  7.64
[11,] 5.25 5.34 5.48 5.73 5.97 6.14 6.47 6.63 6.88  7.31  7.69
[12,] 5.24 5.37 5.47 5.73 5.98 6.16 6.42 6.61 6.88  7.45  7.70
> 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] 5.230000 5.303333 5.443333 5.620833 5.845833 6.080833 6.346667 6.540000
 [9] 6.788333 7.101667 7.612500
> arr.sd
 [1] 0.01279204 0.03498918 0.02933609 0.08586018 0.08638796 0.05696224
 [7] 0.08978088 0.06000000 0.08155682 0.15752826 0.06283094
> arr.range
 [1] 0.04 0.11 0.10 0.25 0.26 0.17 0.28 0.16 0.24 0.53 0.21
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -0.11296      0.02946  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -9.398          3.611  

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

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

Coefficients:
(Intercept)     arr.mean  
    -0.3982       0.0991  

> postscript(file="/var/www/html/rcomp/tmp/14hvo1263634714.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/2a73k1263634714.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/3rcv01263634714.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4mqhz1263634714.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/59yp61263634714.tab") 
> 
> try(system("convert tmp/14hvo1263634714.ps tmp/14hvo1263634714.png",intern=TRUE))
character(0)
> try(system("convert tmp/2a73k1263634714.ps tmp/2a73k1263634714.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.516   0.293   0.807