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(175.348,154.439,136.186,113.662,106.157,100.546,98.314,118.179,112.295,126.938,130.92,181.279,180.389,146.917,150.597,124.222,101.554,102.138,110.315,111.015,105.017,119.888,127.623,149.415,159.755,139.737,136.283,101.952,104.044,96.712,100.665,103.699,103.765,122.732,127.297,160.278,191.784,155.375,142.616,115.331,102.136,95.205,101.566,105.273,117.394,121.148,116.666,154.841,177.74,154.427,133.159,118.102,101.361,101.345,102.233,108.522,101.939,118.405,125.06,178,167.714,143.582,139.259,104.674,103.722,106.153,106.21,113.986,96.906,107.512,112.616,148.507,130.48,137.436,128.21,97.552,91.55,83.104,84.68,85.98,84.891,89.896,94.835,115.348,131.284,134.701,127.193,87.077,72.744,77.542,78.005,85.329,86.041,96.384,116.678,160.672,152.364,144.936,122.974,94.456,82.491,84.89,85.277,81.206,71.012,87.302,97.427,133.242,137.064,119.042,116.47,96.028,79.281,73.872,80.964,86.739,89.997,96.292,101.355,136.543)
> 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] 120
> (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]
 [1,] 175.348 180.389 159.755 191.784 177.740 167.714 130.480 131.284 152.364
 [2,] 154.439 146.917 139.737 155.375 154.427 143.582 137.436 134.701 144.936
 [3,] 136.186 150.597 136.283 142.616 133.159 139.259 128.210 127.193 122.974
 [4,] 113.662 124.222 101.952 115.331 118.102 104.674  97.552  87.077  94.456
 [5,] 106.157 101.554 104.044 102.136 101.361 103.722  91.550  72.744  82.491
 [6,] 100.546 102.138  96.712  95.205 101.345 106.153  83.104  77.542  84.890
 [7,]  98.314 110.315 100.665 101.566 102.233 106.210  84.680  78.005  85.277
 [8,] 118.179 111.015 103.699 105.273 108.522 113.986  85.980  85.329  81.206
 [9,] 112.295 105.017 103.765 117.394 101.939  96.906  84.891  86.041  71.012
[10,] 126.938 119.888 122.732 121.148 118.405 107.512  89.896  96.384  87.302
[11,] 130.920 127.623 127.297 116.666 125.060 112.616  94.835 116.678  97.427
[12,] 181.279 149.415 160.278 154.841 178.000 148.507 115.348 160.672 133.242
        [,10]
 [1,] 137.064
 [2,] 119.042
 [3,] 116.470
 [4,]  96.028
 [5,]  79.281
 [6,]  73.872
 [7,]  80.964
 [8,]  86.739
 [9,]  89.997
[10,]  96.292
[11,] 101.355
[12,] 136.543
> 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] 129.5219 127.4242 121.4099 126.6112 126.6911 120.9034 101.9968 104.4708
 [9] 103.1314 101.1372
> arr.sd
 [1] 27.78023 24.57943 23.19897 28.82052 28.63536 22.70010 20.14760 28.54486
 [9] 27.66711 21.55134
> arr.range
 [1] 82.965 78.835 63.566 96.579 76.655 70.808 54.332 87.928 81.352 63.192
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    13.4454       0.1024  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       0.8805         0.4935  

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

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

Coefficients:
(Intercept)     arr.mean  
    26.8962       0.4189  

> postscript(file="/var/www/rcomp/tmp/1i4to1292944371.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/2i4to1292944371.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/3l5rc1292944371.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/47nqi1292944371.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5s6o61292944371.tab") 
> 
> try(system("convert tmp/1i4to1292944371.ps tmp/1i4to1292944371.png",intern=TRUE))
character(0)
> try(system("convert tmp/2i4to1292944371.ps tmp/2i4to1292944371.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.610   0.170   0.762