R version 2.12.1 (2010-12-16)
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(1664.81,2397.53,2840.71,3547.29,3752.96,3714.74,4349.61,3566.34,5021.82,6423.48,7600.60,19756.21,2499.81,5198.24,7225.14,4806.03,5900.88,4951.34,6179.12,4752.15,5496.43,5835.10,12600.08,28541.72,4717.02,5702.63,9957.58,5304.78,6492.43,6630.80,7349.62,8176.62,8573.17,9690.50,15151.84,34061.01,5921.10,5814.58,12421.25,6369.77,7609.12,7224.75,8121.22,7979.25,8093.06,8476.70,17914.66,30114.41,4826.64,6470.23,9638.77,8821.17,8722.37,10209.48,11276.55,12552.22,11637.39,13606.89,21822.11,45060.69,7615.03,9849.69,14558.40,11587.33,9332.56,13082.09,16732.78,19888.61,23933.38,25391.35,36024.80,80721.71,10243.24,11266.88,21826.84,17357.33,15997.79,18601.53,26155.15,28586.52,30505.41,30821.33,46634.38,104660.67)
> 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] 84
> (np <- floor(n / par1))
[1] 7
> 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]
 [1,]  1664.81  2499.81  4717.02  5921.10  4826.64  7615.03  10243.24
 [2,]  2397.53  5198.24  5702.63  5814.58  6470.23  9849.69  11266.88
 [3,]  2840.71  7225.14  9957.58 12421.25  9638.77 14558.40  21826.84
 [4,]  3547.29  4806.03  5304.78  6369.77  8821.17 11587.33  17357.33
 [5,]  3752.96  5900.88  6492.43  7609.12  8722.37  9332.56  15997.79
 [6,]  3714.74  4951.34  6630.80  7224.75 10209.48 13082.09  18601.53
 [7,]  4349.61  6179.12  7349.62  8121.22 11276.55 16732.78  26155.15
 [8,]  3566.34  4752.15  8176.62  7979.25 12552.22 19888.61  28586.52
 [9,]  5021.82  5496.43  8573.17  8093.06 11637.39 23933.38  30505.41
[10,]  6423.48  5835.10  9690.50  8476.70 13606.89 25391.35  30821.33
[11,]  7600.60 12600.08 15151.84 17914.66 21822.11 36024.80  46634.38
[12,] 19756.21 28541.72 34061.01 30114.41 45060.69 80721.71 104660.67
> 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]  5386.342  7832.170 10150.667 10504.989 13720.376 22393.144 30221.423
> arr.sd
[1]  4815.686  6942.676  8032.665  7034.692 10741.480 20110.766 25516.349
> arr.range
[1] 18091.40 26041.91 29343.99 24299.83 40234.05 73106.68 94417.43
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   -654.435        0.876  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -0.2335         1.0037  

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

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

Coefficients:
(Intercept)     arr.mean  
  -2526.724        3.225  

> postscript(file="/var/www/rcomp/tmp/146891304936217.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/2dqaw1304936217.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/3najg1304936217.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/42m5o1304936217.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/50ign1304936217.tab") 
> 
> try(system("convert tmp/146891304936217.ps tmp/146891304936217.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dqaw1304936217.ps tmp/2dqaw1304936217.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.836   0.204   1.028