R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(95870,95523,95208,94541,101097,100781,95870,92581,92928,92928,93244,93910,93559,96190,97172,96190,99799,97488,92261,90964,90964,91599,89004,90964,89319,90964,93559,94541,96852,95870,89981,87670,86692,87670,86057,86692,84728,88021,89635,89981,96190,96190,88021,86057,86057,87039,82764,80799,78524,79186,82133,79821,86057,87039,80799,78524,77221,78524,74910,73613,68390,69688,70004,70355,76559,75893,68390,65097,63799,65444,59208,54964,47115,47777,47777,47115,52684,53004,46448,45151,42524,46133,39577,35653,28146,29764,27800,28462,33373,34355,31093,30742,30742,35017,27484,22573,14058,20929,19946,20293,28146,27164,23555,25204,25204,31093,24222,20293,14058,22258,21595,21911,28782,28146,25835,26186,27800,31409,25835,21275)
> 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,]  95870 93559 89319 84728 78524 68390 47115 28146 14058 14058
 [2,]  95523 96190 90964 88021 79186 69688 47777 29764 20929 22258
 [3,]  95208 97172 93559 89635 82133 70004 47777 27800 19946 21595
 [4,]  94541 96190 94541 89981 79821 70355 47115 28462 20293 21911
 [5,] 101097 99799 96852 96190 86057 76559 52684 33373 28146 28782
 [6,] 100781 97488 95870 96190 87039 75893 53004 34355 27164 28146
 [7,]  95870 92261 89981 88021 80799 68390 46448 31093 23555 25835
 [8,]  92581 90964 87670 86057 78524 65097 45151 30742 25204 26186
 [9,]  92928 90964 86692 86057 77221 63799 42524 30742 25204 27800
[10,]  92928 91599 87670 87039 78524 65444 46133 35017 31093 31409
[11,]  93244 89004 86057 82764 74910 59208 39577 27484 24222 25835
[12,]  93910 90964 86692 80799 73613 54964 35653 22573 20293 21275
> 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] 95373.42 93846.17 90488.92 87956.83 79695.92 67315.92 45913.17 29962.58
 [9] 23342.25 24590.83
> arr.sd
 [1] 2855.154 3394.644 3831.801 4662.992 3953.920 6197.517 4896.942 3437.513
 [9] 4549.314 4633.531
> arr.range
 [1]  8516 10795 10795 15391 13426 21595 17351 12444 17035 17351
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  4.872e+03   -9.878e-03  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       9.4827        -0.1054  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.893e+04   -6.982e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/13ue11310906392.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/wessaorg/rcomp/tmp/2p4j71310906392.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/3jhwc1310906392.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/461ym1310906392.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/wessaorg/rcomp/tmp/5nq5s1310906392.tab") 
> 
> try(system("convert tmp/13ue11310906392.ps tmp/13ue11310906392.png",intern=TRUE))
character(0)
> try(system("convert tmp/2p4j71310906392.ps tmp/2p4j71310906392.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.638   0.106   0.737