R version 2.7.1 (2008-06-23)
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.

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(100.58,118.48,79.58,81.97,127.13,120.76,120.26,74.9,67.59,87.73,102.87,144.94,110.48,96.34,100.43,90.88,128.28,101.21,73.76,73.64,66.4,57.34,113.59,123.53,102.87,102.99,95.8,98.43,102.65,129.55,100.37,101.93,101.94,93.87,100.91,92.64,101.67,88.67,129.86,98.07,166.45,176.52,82.07,92.18,95.02,84.69,103.01,107.9,204.13,101.99,119.23,95.65,160.95,111.06,150.41,94.79,160.34,104.08,101.07,111.5,136.9,141.71,153.98,134.27,124.71,72.89,101.2,73.28,174.05,111.9,97.06,105.23,109.13,84.04,118.82,90.84,144.28,110.16,86.09,59.87,108.97,94.93,87.36,143.52,108.7,121.13,210.25,110.2,161.46,99.41,132.72,174.29,69.93,83.43,127.53,187.58)
> 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] 96
> (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,] 100.58 127.13  67.59 110.48 128.28  66.40 102.87 102.65 101.94 101.67
[2,] 118.48 120.76  87.73  96.34 101.21  57.34 102.99 129.55  93.87  88.67
[3,]  79.58 120.26 102.87 100.43  73.76 113.59  95.80 100.37 100.91 129.86
[4,]  81.97  74.90 144.94  90.88  73.64 123.53  98.43 101.93  92.64  98.07
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
[1,] 166.45  95.02 204.13 160.95 160.34 136.90 124.71 174.05 109.13 144.28
[2,] 176.52  84.69 101.99 111.06 104.08 141.71  72.89 111.90  84.04 110.16
[3,]  82.07 103.01 119.23 150.41 101.07 153.98 101.20  97.06 118.82  86.09
[4,]  92.18 107.90  95.65  94.79 111.50 134.27  73.28 105.23  90.84  59.87
      [,21]  [,22]  [,23]  [,24]
[1,] 108.97 108.70 161.46  69.93
[2,]  94.93 121.13  99.41  83.43
[3,]  87.36 210.25 132.72 127.53
[4,] 143.52 110.20 174.29 187.58
> 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]  95.1525 110.7625 100.7825  99.5325  94.2225  90.2150 100.0225 108.6250
 [9]  97.3400 104.5675 129.3050  97.6550 130.2500 129.3025 119.2475 141.7150
[17]  93.0200 122.0600 100.7075 100.1000 108.6950 137.5700 141.9700 117.1175
> arr.sd
 [1] 18.165086 24.112006 32.794066  8.280722 26.147605 33.187345  3.525142
 [8] 13.982421  4.762205 17.729957 49.052414 10.143479 50.250978 31.469521
[15] 27.743419  8.737706 24.940282 35.187283 16.064187 35.906401 24.883152
[22] 48.769013 33.273406 53.024811
> arr.range
 [1]  38.90  52.23  77.35  19.60  54.64  66.19   7.19  29.18   9.30  41.19
[11]  94.45  23.21 108.48  66.16  59.27  19.71  51.82  76.99  34.78  84.41
[21]  56.16 101.55  74.88 117.65
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -19.1749       0.4091  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -6.077          1.944  

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

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

Coefficients:
(Intercept)     arr.mean  
   -37.8535       0.8516  

> postscript(file="/var/www/html/rcomp/tmp/1hz7n1219065137.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/2v8v21219065137.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/32al71219065138.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/435mp1219065138.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/520v91219065138.tab") 
> 
> system("convert tmp/1hz7n1219065137.ps tmp/1hz7n1219065137.png")
> system("convert tmp/2v8v21219065137.ps tmp/2v8v21219065137.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.743   0.297   0.956