R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(7.4271,7.7662,7.6289,7.5281,7.3831,7.2355,7.0617,7.1237,7.4533,7.5411,7.4978,7.3525,7.3862,7.311,7.2013,7.249,7.3321,7.59,7.9082,8.2123,8.0929,8.118,8.1206,8.2883,8.4281,8.7917,8.9168,8.9446,8.9786,9.5862,9.6533,9.4125,9.2195,9.2882,9.6774,9.6857,10.1688,10.4399,10.4675,10.149,9.9163,9.9268,10.0529,10.1622,10.083,10.1134,10.3423,10.7536,11.0967,10.8588,10.7719,10.9262,10.708,10.5062,10.0683,9.8954,9.9589,9.9177,9.7189,9.5273,9.5746,9.763,9.6117,9.6581,9.8361,10.2353,10.1285,10.1347,10.2141,10.0971,9.9651,10.1286,10.3356,10.1238,10.1326,10.2467,10.44,10.3689,10.2415,10.3899,10.3162,10.4533,10.6741,10.8957,10.7404,10.6568,10.5682,10.9833,11.0237,10.8462,10.7287,10.7809,10.2609,9.8252,9.1071,8.695,9.2205,9.0496,8.7406,8.921,9.011,9.3157,9.5786,9.6246,9.7485,9.9431,10.1152,10.1827,9.9777,9.7436,9.3462,9.2623,9.1505,8.5794,8.3245,8.6538,8.752,8.8104,9.2665,9.0895)
> 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,] 7.4271 7.3862 8.4281 10.1688 11.0967  9.5746 10.3356 10.7404  9.2205
 [2,] 7.7662 7.3110 8.7917 10.4399 10.8588  9.7630 10.1238 10.6568  9.0496
 [3,] 7.6289 7.2013 8.9168 10.4675 10.7719  9.6117 10.1326 10.5682  8.7406
 [4,] 7.5281 7.2490 8.9446 10.1490 10.9262  9.6581 10.2467 10.9833  8.9210
 [5,] 7.3831 7.3321 8.9786  9.9163 10.7080  9.8361 10.4400 11.0237  9.0110
 [6,] 7.2355 7.5900 9.5862  9.9268 10.5062 10.2353 10.3689 10.8462  9.3157
 [7,] 7.0617 7.9082 9.6533 10.0529 10.0683 10.1285 10.2415 10.7287  9.5786
 [8,] 7.1237 8.2123 9.4125 10.1622  9.8954 10.1347 10.3899 10.7809  9.6246
 [9,] 7.4533 8.0929 9.2195 10.0830  9.9589 10.2141 10.3162 10.2609  9.7485
[10,] 7.5411 8.1180 9.2882 10.1134  9.9177 10.0971 10.4533  9.8252  9.9431
[11,] 7.4978 8.1206 9.6774 10.3423  9.7189  9.9651 10.6741  9.1071 10.1152
[12,] 7.3525 8.2883 9.6857 10.7536  9.5273 10.1286 10.8957  8.6950 10.1827
       [,10]
 [1,] 9.9777
 [2,] 9.7436
 [3,] 9.3462
 [4,] 9.2623
 [5,] 9.1505
 [6,] 8.5794
 [7,] 8.3245
 [8,] 8.6538
 [9,] 8.7520
[10,] 8.8104
[11,] 9.2665
[12,] 9.0895
> 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]  7.416583  7.734158  9.215217 10.214642 10.329525  9.945575 10.384858
 [8] 10.351367  9.454258  9.079700
> arr.sd
 [1] 0.2029436 0.4256799 0.4074278 0.2442451 0.5372453 0.2447950 0.2197499
 [8] 0.7562798 0.4829110 0.4836850
> arr.range
 [1] 0.7045 1.0870 1.2576 0.8373 1.5694 0.6607 0.7719 2.3287 1.4421 1.6532
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    0.04195      0.03809  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -2.6611         0.7415  

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

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

Coefficients:
(Intercept)     arr.mean  
   -0.04515      0.13560  

> postscript(file="/var/www/html/rcomp/tmp/14zh41293376150.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/rcomp/tmp/2f8yp1293376150.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/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/3i9wv1293376150.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/439dj1293376150.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5pabp1293376150.tab") 
> 
> try(system("convert tmp/14zh41293376150.ps tmp/14zh41293376150.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f8yp1293376150.ps tmp/2f8yp1293376150.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.495   0.275   1.248