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(66857.2,64722.8,68489.6,71342.9,63542.5,69425.0,58927.9,61009.0,66837.0,66147.6,65982.3,65527.5,65914.6,59189.9,66211.4,66400.8,60167.7,64547.9,57706.2,58642.6,60082.1,63414.8,66044.0,57628.5,62838.8,55758.6,61004.5,66173.4,57489.0,59552.2,57061.8,55895.3,56314.7,61232.8,60014.1,57685.4,60403.1,52349.7,55693.3,65676.1,54898.8,55518.2,53779.1,52340.9,55704.4,60330.3,52837.4,55388.1,60383.4,52070.3,54077.0,62887.8,49212.8,57722.0,53936.8,46991.0,54984.2,56485.1,51277.8,53596.4,54252.5,49413.0,53213.2,58695.3,48723.5,54510.0,49454.1,46136.6,54622.5,50583.0,53224.3,53056.4)
> 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] 72
> (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,] 66857.2 63542.5 66837.0 65914.6 60167.7 60082.1 62838.8 57489.0 56314.7
[2,] 64722.8 69425.0 66147.6 59189.9 64547.9 63414.8 55758.6 59552.2 61232.8
[3,] 68489.6 58927.9 65982.3 66211.4 57706.2 66044.0 61004.5 57061.8 60014.1
[4,] 71342.9 61009.0 65527.5 66400.8 58642.6 57628.5 66173.4 55895.3 57685.4
       [,10]   [,11]   [,12]   [,13]   [,14]   [,15]   [,16]   [,17]   [,18]
[1,] 60403.1 54898.8 55704.4 60383.4 49212.8 54984.2 54252.5 48723.5 54622.5
[2,] 52349.7 55518.2 60330.3 52070.3 57722.0 56485.1 49413.0 54510.0 50583.0
[3,] 55693.3 53779.1 52837.4 54077.0 53936.8 51277.8 53213.2 49454.1 53224.3
[4,] 65676.1 52340.9 55388.1 62887.8 46991.0 53596.4 58695.3 46136.6 53056.4
> 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] 67853.12 63226.10 66123.60 64429.18 60266.10 61792.35 61443.82 57499.57
 [9] 58811.75 58530.55 54134.25 56065.05 57354.62 51965.65 54085.88 53893.50
[17] 49706.05 52871.55
> arr.sd
 [1] 2791.3217 4542.9992  543.0827 3498.5769 3029.4298 3695.5592 4352.3796
 [8] 1525.2023 2221.9400 5797.0746 1395.4796 3119.7442 5113.9163 4807.8520
[15] 2212.7012 3817.6717 3504.6537 1679.4730
> arr.range
 [1]  6620.1 10497.1  1309.5  7210.9  6841.7  8415.5 10414.8  3656.9  4918.1
[10] 13326.4  3177.3  7492.9 10817.5 10731.0  5207.3  9282.3  8373.4  4039.5
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 4121.92703     -0.01576  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      17.3170        -0.8545  

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

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

Coefficients:
(Intercept)     arr.mean  
 10245.5427      -0.0496  

> postscript(file="/var/www/html/rcomp/tmp/133jm1274133620.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/2eu0p1274133620.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/36mzt1274133620.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4amyg1274133620.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/56wwp1274133620.tab") 
> 
> try(system("convert tmp/133jm1274133620.ps tmp/133jm1274133620.png",intern=TRUE))
character(0)
> try(system("convert tmp/2eu0p1274133620.ps tmp/2eu0p1274133620.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.516   0.284   1.166