R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- c(90.2
+ ,90
+ ,88.8
+ ,85.8
+ ,84.2
+ ,80
+ ,77.8
+ ,76.8
+ ,86.4
+ ,89.2
+ ,86.2
+ ,84.6
+ ,83.2
+ ,83.2
+ ,82.6
+ ,79.8
+ ,77.2
+ ,74.8
+ ,73
+ ,73
+ ,83.6
+ ,85.6
+ ,84.8
+ ,84.2
+ ,83.4
+ ,84.6
+ ,84.6
+ ,83.8
+ ,81.2
+ ,79.6
+ ,78
+ ,78.2
+ ,88.8
+ ,92
+ ,91
+ ,91.2
+ ,90.4
+ ,91.8
+ ,92.2
+ ,90.2
+ ,88.6
+ ,87.8
+ ,86
+ ,87.2
+ ,97.6
+ ,101.2
+ ,100.4
+ ,100.2
+ ,100.2
+ ,103
+ ,104.2
+ ,104
+ ,102.4
+ ,101.8
+ ,101
+ ,102.2
+ ,114
+ ,118.4
+ ,118.8
+ ,117.2
+ ,117.2
+ ,118.4
+ ,118.8
+ ,117.2
+ ,114.4
+ ,112.6
+ ,111
+ ,110.8
+ ,120.2
+ ,124.4
+ ,123.4
+ ,121.2
+ ,119
+ ,119.8
+ ,120
+ ,118.4
+ ,115
+ ,113.4
+ ,111
+ ,111
+ ,121.6
+ ,126.2
+ ,125.8
+ ,124.8
+ ,122
+ ,123.2
+ ,124.2
+ ,120.8
+ ,116.8
+ ,114.8
+ ,111
+ ,109
+ ,119.8
+ ,124
+ ,121.6
+ ,118
+ ,115.8
+ ,116
+ ,115.8
+ ,114.4
+ ,112
+ ,110.2
+ ,107.4
+ ,108.2
+ ,117.6
+ ,121.4
+ ,119.8
+ ,115.6
+ ,112.6
+ ,113.2
+ ,112.2
+ ,110.8
+ ,108
+ ,105.2
+ ,102.4
+ ,101
+ ,110.8
+ ,116.8
+ ,113.8
+ ,108
+ ,104.4
+ ,105.2
+ ,105.4
+ ,103.2
+ ,100.6
+ ,97.8
+ ,95.8
+ ,95
+ ,104.8
+ ,110.4
+ ,106.4
+ ,102.2
+ ,98.4
+ ,98.4
+ ,98.6
+ ,96.2
+ ,92.4
+ ,91.4
+ ,88.4
+ ,87.8
+ ,97.6
+ ,104.2
+ ,100.2
+ ,97
+ ,92.8
+ ,92
+ ,93.4
+ ,92
+ ,89.6
+ ,88.6
+ ,87.2
+ ,86.2
+ ,96.8
+ ,102
+ ,102.6
+ ,100.6
+ ,94.2
+ ,94.2
+ ,95.2
+ ,95
+ ,94
+ ,92.2
+ ,91
+ ,91.2
+ ,103.4
+ ,105
+ ,104.6
+ ,103.8
+ ,101.8
+ ,102.4
+ ,103.8
+ ,103.4
+ ,102
+ ,101.8
+ ,100.2
+ ,101.4
+ ,113.8
+ ,116
+ ,115.6
+ ,113
+ ,109.4
+ ,111
+ ,112.4
+ ,112.2
+ ,111
+ ,108.8
+ ,107.4
+ ,108.6
+ ,118.8
+ ,122.2
+ ,122.6
+ ,122.2
+ ,118.8
+ ,119
+ ,118.2
+ ,117.8
+ ,116.8
+ ,114.6
+ ,113.4
+ ,113.8
+ ,124.2
+ ,125.8
+ ,125.6
+ ,122.4
+ ,119
+ ,119.4
+ ,118.6
+ ,118
+ ,116
+ ,114.8
+ ,114.6
+ ,114.6
+ ,124
+ ,125.2
+ ,124
+ ,117.6
+ ,113.2
+ ,111.4
+ ,112.2
+ ,109.8
+ ,106.4
+ ,105.2
+ ,102.2
+ ,99.8
+ ,111
+ ,113
+ ,108.4
+ ,105.4
+ ,102
+ ,102.8
+ ,103.4
+ ,101.6
+ ,98.6
+ ,98
+ ,93.8
+ ,95.6
+ ,105.6
+ ,106.8
+ ,103.6
+ ,101.2
+ ,100.4
+ ,103.2
+ ,105.6
+ ,106.6
+ ,107.2
+ ,107.4
+ ,104.8
+ ,107.2
+ ,117.4
+ ,119.4
+ ,116.2
+ ,112.8
+ ,111.6)
> 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] 253
> (np <- floor(n / par1))
[1] 21
> 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] [,11] [,12]
 [1,] 90.2 83.2 83.4  90.4 100.2 117.2 119.0 122.0 115.8 112.6 104.4  98.4
 [2,] 90.0 83.2 84.6  91.8 103.0 118.4 119.8 123.2 116.0 113.2 105.2  98.4
 [3,] 88.8 82.6 84.6  92.2 104.2 118.8 120.0 124.2 115.8 112.2 105.4  98.6
 [4,] 85.8 79.8 83.8  90.2 104.0 117.2 118.4 120.8 114.4 110.8 103.2  96.2
 [5,] 84.2 77.2 81.2  88.6 102.4 114.4 115.0 116.8 112.0 108.0 100.6  92.4
 [6,] 80.0 74.8 79.6  87.8 101.8 112.6 113.4 114.8 110.2 105.2  97.8  91.4
 [7,] 77.8 73.0 78.0  86.0 101.0 111.0 111.0 111.0 107.4 102.4  95.8  88.4
 [8,] 76.8 73.0 78.2  87.2 102.2 110.8 111.0 109.0 108.2 101.0  95.0  87.8
 [9,] 86.4 83.6 88.8  97.6 114.0 120.2 121.6 119.8 117.6 110.8 104.8  97.6
[10,] 89.2 85.6 92.0 101.2 118.4 124.4 126.2 124.0 121.4 116.8 110.4 104.2
[11,] 86.2 84.8 91.0 100.4 118.8 123.4 125.8 121.6 119.8 113.8 106.4 100.2
[12,] 84.6 84.2 91.2 100.2 117.2 121.2 124.8 118.0 115.6 108.0 102.2  97.0
      [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
 [1,]  92.8  94.2 101.8 109.4 118.8 119.0 113.2 102.0 100.4
 [2,]  92.0  94.2 102.4 111.0 119.0 119.4 111.4 102.8 103.2
 [3,]  93.4  95.2 103.8 112.4 118.2 118.6 112.2 103.4 105.6
 [4,]  92.0  95.0 103.4 112.2 117.8 118.0 109.8 101.6 106.6
 [5,]  89.6  94.0 102.0 111.0 116.8 116.0 106.4  98.6 107.2
 [6,]  88.6  92.2 101.8 108.8 114.6 114.8 105.2  98.0 107.4
 [7,]  87.2  91.0 100.2 107.4 113.4 114.6 102.2  93.8 104.8
 [8,]  86.2  91.2 101.4 108.6 113.8 114.6  99.8  95.6 107.2
 [9,]  96.8 103.4 113.8 118.8 124.2 124.0 111.0 105.6 117.4
[10,] 102.0 105.0 116.0 122.2 125.8 125.2 113.0 106.8 119.4
[11,] 102.6 104.6 115.6 122.6 125.6 124.0 108.4 103.6 116.2
[12,] 100.6 103.8 113.0 122.2 122.4 117.6 105.4 101.2 112.8
> 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]  85.00000  80.41667  84.70000  92.80000 107.26667 117.46667 118.83333
 [8] 118.76667 114.51667 109.56667 102.60000  95.88333  93.65000  96.98333
[15] 106.26667 113.88333 119.20000 118.81667 108.16667 101.08333 109.01667
> arr.sd
 [1] 4.602766 4.700838 5.044889 5.561556 7.432769 4.540992 5.355597 5.010413
 [9] 4.337958 4.780136 4.567872 4.914882 5.667210 5.506663 6.265248 5.846807
[17] 4.396693 3.774034 4.383302 3.903805 6.004519
> arr.range
 [1] 13.4 12.6 14.0 15.2 18.6 13.6 15.2 15.2 14.0 15.8 15.4 16.4 16.4 14.0 15.8
[16] 15.2 12.4 10.6 13.4 13.0 19.0
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
   5.561254    -0.004641  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       2.0809        -0.1011  

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

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

Coefficients:
(Intercept)     arr.mean  
 14.7674764   -0.0004178  

> postscript(file="/var/www/html/rcomp/tmp/1mohc1261298275.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/25ahj1261298275.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/3yzaa1261298275.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/484wg1261298275.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5r8nh1261298275.tab") 
> 
> try(system("convert tmp/1mohc1261298275.ps tmp/1mohc1261298275.png",intern=TRUE))
character(0)
> try(system("convert tmp/25ahj1261298275.ps tmp/25ahj1261298275.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.530   0.289   8.625