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(423.4,404.1,500,472.6,496.1,562,434.8,538.2,577.6,518.1,625.2,561.2,523.3,536.1,607.3,637.3,606.9,652.9,617.2,670.4,729.9,677.2,710,844.3,748.2,653.9,742.6,854.2,808.4,1819,1936.5,1966.1,2083.1,1620.1,1527.6,1795,1685.1,1851.8,2164.4,1981.8,1726.5,2144.6,1758.2,1672.9,1837.3,1596.1,1446,1898.4,1964.1,1755.9,2255.3,1881.2,2117.9,1656.5,1544.1,2098.9,2133.3,1963.5,1801.2,2365.4,1936.5,1667.6,1983.5,2058.6,2448.3,1858.1,1625.4,2130.6,2515.7,2230.2,2086.9,2235,2100.2,2288.6,2490,2573.7,2543.8,2004.7,2390,2338.4,2724.5,2292.5,2386,2477.9,2337,2605.1,2560.8,2839.3,2407.2,2085.2,2735.6,2798.7,3053.2,2405,2471.9,2727.3,2790.7,2385.4,3206.6,2705.6,3518.4,1954.9,2584.3,2535.8,2685.9,2866,2236.6,2934.9,2668.6,2371.2,3165.9,2887.2,3112.2,2671.2,2432.6,2812.3,3095.7,2862.9,2607.3,2862.5)
> 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]  [,10]
 [1,] 423.4 523.3  748.2 1685.1 1964.1 1936.5 2100.2 2337.0 2790.7 2668.6
 [2,] 404.1 536.1  653.9 1851.8 1755.9 1667.6 2288.6 2605.1 2385.4 2371.2
 [3,] 500.0 607.3  742.6 2164.4 2255.3 1983.5 2490.0 2560.8 3206.6 3165.9
 [4,] 472.6 637.3  854.2 1981.8 1881.2 2058.6 2573.7 2839.3 2705.6 2887.2
 [5,] 496.1 606.9  808.4 1726.5 2117.9 2448.3 2543.8 2407.2 3518.4 3112.2
 [6,] 562.0 652.9 1819.0 2144.6 1656.5 1858.1 2004.7 2085.2 1954.9 2671.2
 [7,] 434.8 617.2 1936.5 1758.2 1544.1 1625.4 2390.0 2735.6 2584.3 2432.6
 [8,] 538.2 670.4 1966.1 1672.9 2098.9 2130.6 2338.4 2798.7 2535.8 2812.3
 [9,] 577.6 729.9 2083.1 1837.3 2133.3 2515.7 2724.5 3053.2 2685.9 3095.7
[10,] 518.1 677.2 1620.1 1596.1 1963.5 2230.2 2292.5 2405.0 2866.0 2862.9
[11,] 625.2 710.0 1527.6 1446.0 1801.2 2086.9 2386.0 2471.9 2236.6 2607.3
[12,] 561.2 844.3 1795.0 1898.4 2365.4 2235.0 2477.9 2727.3 2934.9 2862.5
> 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]  509.4417  651.0667 1379.5583 1813.5917 1961.4417 2064.7000 2384.1917
 [8] 2585.5250 2700.4250 2795.8000
> arr.sd
 [1]  67.47709  86.77630 566.31150 213.09946 245.68691 274.39194 200.34490
 [8] 263.12318 418.53049 256.55712
> arr.range
 [1]  221.1  321.0 1429.2  718.4  821.3  890.3  719.8  968.0 1563.5  794.7
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  123.89383      0.07181  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -0.5681         0.8044  

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

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

Coefficients:
(Intercept)     arr.mean  
   278.0084       0.3007  

> postscript(file="/var/www/html/rcomp/tmp/1fn2r1259187291.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/20lvp1259187291.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/3qsr41259187291.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4dsdp1259187291.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5816w1259187291.tab") 
> system("convert tmp/1fn2r1259187291.ps tmp/1fn2r1259187291.png")
> system("convert tmp/20lvp1259187291.ps tmp/20lvp1259187291.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.511   0.272   0.652