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(17848,19592,21092,20889,25890,24965,22225,20977,22897,22785,22769,19637,20203,20450,23083,21738,26766,25280,22574,22729,21378,22902,24989,21116,15169,15846,20927,18273,22538,15596,14034,11366,14861,15149,13577,13026,13190,13196,15826,14733,16307,15703,14589,12043,15057,14053,12698,10888,10045,11549,13767,12424,13116,14211,12266,12602,15714,13742,12745,10491,10057,10900,11771,11992,11993,14504,11727,11477,13578,11555,11846,11397,10066,10269,14279,13870,13695,14420,11424,9704,12464,14301,13464,9893,11572,12380,16692,16052,16459,14761,13654,13480,18068,16560,14530,10650,11651,13735,13360,17818,20613,16231,13862,12004,17734,15034,12609,12320,10833,11350,13648,14890,16325,18045,15616,11926,16855,15083,12520,12355)
> 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,] 17848 20203 15169 13190 10045 10057 10066 11572 11651 10833
 [2,] 19592 20450 15846 13196 11549 10900 10269 12380 13735 11350
 [3,] 21092 23083 20927 15826 13767 11771 14279 16692 13360 13648
 [4,] 20889 21738 18273 14733 12424 11992 13870 16052 17818 14890
 [5,] 25890 26766 22538 16307 13116 11993 13695 16459 20613 16325
 [6,] 24965 25280 15596 15703 14211 14504 14420 14761 16231 18045
 [7,] 22225 22574 14034 14589 12266 11727 11424 13654 13862 15616
 [8,] 20977 22729 11366 12043 12602 11477  9704 13480 12004 11926
 [9,] 22897 21378 14861 15057 15714 13578 12464 18068 17734 16855
[10,] 22785 22902 15149 14053 13742 11555 14301 16560 15034 15083
[11,] 22769 24989 13577 12698 12745 11846 13464 14530 12609 12520
[12,] 19637 21116 13026 10888 10491 11397  9893 10650 12320 12355
> 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] 21797.17 22767.33 15863.50 14023.58 12722.67 11899.75 12320.75 14571.50
 [9] 14747.58 14120.50
> arr.sd
 [1] 2280.732 2023.898 3232.188 1653.273 1575.036 1152.496 1921.608 2289.886
 [9] 2801.778 2348.986
> arr.range
 [1]  8042  6563 11172  5419  5669  4447  4716  7418  8962  7212
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  1.401e+03    4.693e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       2.2767         0.5557  

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

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

Coefficients:
(Intercept)     arr.mean  
  3932.0380       0.1957  

> postscript(file="/var/www/html/rcomp/tmp/10wej1291372517.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/2bne41291372517.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/37gfn1291372518.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4azwt1291372518.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5vhuz1291372518.tab") 
> 
> try(system("convert tmp/10wej1291372517.ps tmp/10wej1291372517.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bne41291372517.ps tmp/2bne41291372517.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.509   0.305   2.032