R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(11178.4,9516.4,12102.8,12989.0,11610.2,10205.5,11356.2,11307.1,12648.6,11947.2,11714.1,12192.5,11268.8,9097.4,12639.8,13040.1,11687.3,11191.7,11391.9,11793.1,13933.2,12778.1,11810.3,13698.4,11956.6,10723.8,13938.9,13979.8,13807.4,12973.9,12509.8,12934.1,14908.3,13772.1,13012.6,14049.9,11816.5,11593.2,14466.2,13615.9,14733.9,13880.7,13527.5,13584.0,16170.2,13260.6,14741.9,15486.5,13154.5,12621.2,15031.6,15452.4,15428,13105.9,14716.8,14180.0,16202.2,14392.4,15140.6,15960.1,14351.3,13230.2,15202.1,17157.3,16159.1,13405.7,17224.7,17338.4,17370.6,18817.8,16593.2,17979.5,17015.2)
> 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] 73
> (np <- floor(n / par1))
[1] 18
> 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,] 11178.4 11610.2 12648.6 11268.8 11687.3 13933.2 11956.6 13807.4 14908.3
[2,]  9516.4 10205.5 11947.2  9097.4 11191.7 12778.1 10723.8 12973.9 13772.1
[3,] 12102.8 11356.2 11714.1 12639.8 11391.9 11810.3 13938.9 12509.8 13012.6
[4,] 12989.0 11307.1 12192.5 13040.1 11793.1 13698.4 13979.8 12934.1 14049.9
       [,10]   [,11]   [,12]   [,13]   [,14]   [,15]   [,16]   [,17]   [,18]
[1,] 11816.5 14733.9 16170.2 13154.5 15428.0 16202.2 14351.3 16159.1 17370.6
[2,] 11593.2 13880.7 13260.6 12621.2 13105.9 14392.4 13230.2 13405.7 18817.8
[3,] 14466.2 13527.5 14741.9 15031.6 14716.8 15140.6 15202.1 17224.7 16593.2
[4,] 13615.9 13584.0 15486.5 15452.4 14180.0 15960.1 17157.3 17338.4 17979.5
> 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] 11446.65 11119.75 12125.60 11511.52 11516.00 13055.00 12649.77 13056.30
 [9] 13935.73 12872.95 13931.52 14914.80 14064.92 14357.67 15423.83 14985.23
[17] 16031.98 17690.28
> arr.sd
 [1] 1484.0485  623.8063  399.6513 1779.1815  274.8936  968.0135 1593.8090
 [8]  542.9966  782.7028 1395.7396  556.8958 1247.5499 1387.1749  978.6173
[15]  824.1182 1658.0026 1829.6466  941.7589
> arr.range
 [1] 3472.6 1404.7  934.5 3942.7  601.4 2122.9 3256.0 1297.6 1895.7 2873.0
[11] 1206.4 2909.6 2831.2 2322.1 1809.8 3927.1 3932.7 2224.6
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  389.55812      0.05009  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       -4.354          1.178  

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

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

Coefficients:
(Intercept)     arr.mean  
   701.9826       0.1239  

> postscript(file="/var/www/html/freestat/rcomp/tmp/1balz1228761297.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/freestat/rcomp/tmp/2nuab1228761297.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/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/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/freestat/rcomp/tmp/3c4po1228761297.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/4b8v61228761297.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/freestat/rcomp/tmp/5oxd91228761297.tab") 
> 
> system("convert tmp/1balz1228761297.ps tmp/1balz1228761297.png")
> system("convert tmp/2nuab1228761297.ps tmp/2nuab1228761297.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.766   0.426   1.800