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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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
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(93.2
+ ,96
+ ,95.2
+ ,77.1
+ ,70.9
+ ,64.8
+ ,70.1
+ ,77.3
+ ,79.5
+ ,100.6
+ ,100.7
+ ,107.1
+ ,95.9
+ ,82.8
+ ,83.3
+ ,80
+ ,80.4
+ ,67.5
+ ,75.7
+ ,71.1
+ ,89.3
+ ,101.1
+ ,105.2
+ ,114.1
+ ,96.3
+ ,84.4
+ ,91.2
+ ,81.9
+ ,80.5
+ ,70.4
+ ,74.8
+ ,75.9
+ ,86.3
+ ,98.7
+ ,100.9
+ ,113.8
+ ,89.8
+ ,84.4
+ ,87.2
+ ,85.6
+ ,72
+ ,69.2
+ ,77.5
+ ,78.1
+ ,94.3
+ ,97.7
+ ,100.2
+ ,116.4
+ ,97.1
+ ,93
+ ,96
+ ,80.5
+ ,76.1
+ ,69.9
+ ,73.6
+ ,92.6
+ ,94.2
+ ,93.5
+ ,108.5
+ ,109.4
+ ,105.1
+ ,92.5
+ ,97.1
+ ,81.4
+ ,79.1
+ ,72.1
+ ,78.7
+ ,87.1
+ ,91.4
+ ,109.9
+ ,116.3
+ ,113
+ ,100
+ ,84.8
+ ,94.3
+ ,87.1
+ ,90.3
+ ,72.4
+ ,84.9
+ ,92.7
+ ,92.2
+ ,114.9
+ ,112.5
+ ,118.3
+ ,106
+ ,91.2
+ ,96.6
+ ,96.3
+ ,88.2
+ ,70.2
+ ,86.5
+ ,88.2
+ ,102.8
+ ,119.1
+ ,119.2
+ ,125.1
+ ,106.1
+ ,102.1
+ ,105.2
+ ,101
+ ,84.3
+ ,87.5
+ ,92.7
+ ,94.4
+ ,113
+ ,113.9
+ ,122.9
+ ,132.7
+ ,106.9
+ ,96.6
+ ,127.3
+ ,98.2
+ ,100.2
+ ,89.4
+ ,95.3
+ ,104.2
+ ,106.4
+ ,116.2
+ ,135.9
+ ,134
+ ,104.6
+ ,107.1
+ ,123.5
+ ,98.8
+ ,98.6
+ ,90.6
+ ,89.1
+ ,105.2
+ ,114
+ ,122.1
+ ,138
+ ,142.2
+ ,116.4
+ ,112.6
+ ,123.8
+ ,103.6
+ ,113.9
+ ,98.6
+ ,95
+ ,116
+ ,113.9
+ ,127.5
+ ,131.4
+ ,145.9
+ ,131.5
+ ,131
+ ,130.5
+ ,118.9
+ ,114.3
+ ,85.7
+ ,104.6
+ ,105.1
+ ,117.3
+ ,142.5
+ ,140
+ ,159.8
+ ,131.2
+ ,125.4
+ ,126.5
+ ,119.4
+ ,113.5
+ ,98.7
+ ,114.5
+ ,113.8
+ ,133.1
+ ,143.4
+ ,137.3
+ ,165.2
+ ,126.9
+ ,124
+ ,135.7
+ ,130
+ ,109.4
+ ,117.8
+ ,120.3
+ ,121
+ ,132.3
+ ,142.9
+ ,147.4
+ ,175.9
+ ,132.6
+ ,123.7
+ ,153.3
+ ,134
+ ,119.6
+ ,116.2
+ ,118.6
+ ,130.7
+ ,129.3
+ ,144.4
+ ,163.2
+ ,179.4
+ ,128.1
+ ,138.4
+ ,152.7
+ ,120
+ ,140.5
+ ,116.2
+ ,121.4
+ ,127.8
+ ,143.6
+ ,157.6
+ ,166.2
+ ,182.3
+ ,153.1
+ ,147.6
+ ,157.7
+ ,137.2
+ ,151.5
+ ,98.7
+ ,145.8
+ ,151.7
+ ,129.4
+ ,174.1
+ ,197
+ ,193.9
+ ,164.1
+ ,142.8
+ ,157.9
+ ,159.2
+ ,162.2
+ ,123.1
+ ,130
+ ,150.1
+ ,169.4
+ ,179.7
+ ,182.1
+ ,194.3
+ ,161.4
+ ,169.4
+ ,168.8
+ ,158.1
+ ,158.5
+ ,135.3
+ ,149.3
+ ,143.4
+ ,142.2
+ ,188.4
+ ,166.2
+ ,199.2
+ ,182.7
+ ,145.2
+ ,182.1
+ ,158.7
+ ,141.6
+ ,132.6
+ ,139.6
+ ,147
+ ,166.6
+ ,157
+ ,180.4
+ ,210.2
+ ,159.8
+ ,157.8
+ ,168.2
+ ,158.4
+ ,152
+ ,142.2
+ ,137.2
+ ,152.6
+ ,166.8
+ ,165.6
+ ,198.6
+ ,201.5
+ ,170.7
+ ,164.4
+ ,179.7
+ ,157
+ ,168
+ ,139.3
+ ,138.6
+ ,153.4
+ ,138.9
+ ,172.1
+ ,198.4
+ ,217.8
+ ,173.7
+ ,153.8
+ ,175.6
+ ,147.1
+ ,160.3
+ ,135.2
+ ,148.8
+ ,151
+ ,148.2
+ ,182.2
+ ,189.2
+ ,183.1
+ ,170
+ ,158.4
+ ,176.1
+ ,156.2
+ ,153.2
+ ,117.9
+ ,149.8
+ ,156.6
+ ,166.7
+ ,156.8
+ ,158.6
+ ,210.8
+ ,203.6
+ ,175.2
+ ,168.7
+ ,155.9
+ ,147.3
+ ,137
+ ,141.1
+ ,167.4
+ ,160.2
+ ,191.9
+ ,174.4
+ ,208.2
+ ,159.4
+ ,161.1
+ ,172.1
+ ,158.4
+ ,114.6
+ ,159.6
+ ,159.7
+ ,159.4
+ ,160.7
+ ,165.5
+ ,205
+ ,205.2
+ ,141.6
+ ,148.1
+ ,184.9
+ ,132.5
+ ,137.3
+ ,135.5
+ ,121.7
+ ,166.1
+ ,146.8
+ ,162.8
+ ,186.8
+ ,185.5
+ ,151.5
+ ,158.1
+ ,143
+ ,151.2
+ ,147.6
+ ,130.7
+ ,137.5
+ ,146.1
+ ,133.6
+ ,167.9
+ ,181.9
+ ,202
+ ,166.5
+ ,151.3
+ ,146.2
+ ,148.3
+ ,144.7
+ ,123.6
+ ,151.6
+ ,133.9
+ ,137.4
+ ,181.6
+ ,182
+ ,190
+ ,161.2
+ ,155.5
+ ,141.9
+ ,164.6
+ ,136.2
+ ,126.8
+ ,152.5
+ ,126.6
+ ,150.1
+ ,186.3
+ ,147.5
+ ,200.4
+ ,177.2
+ ,127.4
+ ,177.1
+ ,154.4
+ ,135.2
+ ,126.4
+ ,147.3
+ ,140.6
+ ,152.3
+ ,151.2
+ ,172.2
+ ,215.3
+ ,154.1
+ ,159.3
+ ,160.4
+ ,151.9
+ ,148.4
+ ,139.6
+ ,148.2
+ ,153.5
+ ,145.1
+ ,183.7
+ ,210.5
+ ,203.3
+ ,153.3
+ ,144.3
+ ,169.6
+ ,143.7
+ ,160.1
+ ,135.6
+ ,141.8
+ ,159.9
+ ,145.7
+ ,183.5
+ ,198.2
+ ,186.8
+ ,172
+ ,150.6
+ ,163.3
+ ,153.7
+ ,152.9
+ ,135.5
+ ,148.5
+ ,148.4
+ ,133.6
+ ,194.1
+ ,208.6
+ ,197.3
+ ,164.4
+ ,148.1
+ ,152
+ ,144.1
+ ,155
+ ,124.5
+ ,153
+ ,146
+ ,138
+ ,190
+ ,192
+ ,192
+ ,147
+ ,133
+ ,163
+ ,150
+ ,129
+ ,131
+ ,145
+ ,137
+ ,138
+ ,168
+ ,176
+ ,188
+ ,139
+ ,143
+ ,150
+ ,154
+ ,137
+ ,129
+ ,128
+ ,140
+ ,143
+ ,151
+ ,177
+ ,184
+ ,151
+ ,134
+ ,164
+ ,126
+ ,131
+ ,125
+ ,127
+ ,143
+ ,143
+ ,160
+ ,190
+ ,182
+ ,138
+ ,136
+ ,152
+ ,127
+ ,151
+ ,130
+ ,119
+ ,153)
> 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] 476
> (np <- floor(n / par1))
[1] 39
> 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,]  93.2  95.9  96.3  89.8  97.1 105.1 100.0 106.0 106.1 106.9 104.6 116.4
 [2,]  96.0  82.8  84.4  84.4  93.0  92.5  84.8  91.2 102.1  96.6 107.1 112.6
 [3,]  95.2  83.3  91.2  87.2  96.0  97.1  94.3  96.6 105.2 127.3 123.5 123.8
 [4,]  77.1  80.0  81.9  85.6  80.5  81.4  87.1  96.3 101.0  98.2  98.8 103.6
 [5,]  70.9  80.4  80.5  72.0  76.1  79.1  90.3  88.2  84.3 100.2  98.6 113.9
 [6,]  64.8  67.5  70.4  69.2  69.9  72.1  72.4  70.2  87.5  89.4  90.6  98.6
 [7,]  70.1  75.7  74.8  77.5  73.6  78.7  84.9  86.5  92.7  95.3  89.1  95.0
 [8,]  77.3  71.1  75.9  78.1  92.6  87.1  92.7  88.2  94.4 104.2 105.2 116.0
 [9,]  79.5  89.3  86.3  94.3  94.2  91.4  92.2 102.8 113.0 106.4 114.0 113.9
[10,] 100.6 101.1  98.7  97.7  93.5 109.9 114.9 119.1 113.9 116.2 122.1 127.5
[11,] 100.7 105.2 100.9 100.2 108.5 116.3 112.5 119.2 122.9 135.9 138.0 131.4
[12,] 107.1 114.1 113.8 116.4 109.4 113.0 118.3 125.1 132.7 134.0 142.2 145.9
      [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
 [1,] 131.5 131.2 126.9 132.6 128.1 153.1 164.1 161.4 182.7 159.8 170.7 173.7
 [2,] 131.0 125.4 124.0 123.7 138.4 147.6 142.8 169.4 145.2 157.8 164.4 153.8
 [3,] 130.5 126.5 135.7 153.3 152.7 157.7 157.9 168.8 182.1 168.2 179.7 175.6
 [4,] 118.9 119.4 130.0 134.0 120.0 137.2 159.2 158.1 158.7 158.4 157.0 147.1
 [5,] 114.3 113.5 109.4 119.6 140.5 151.5 162.2 158.5 141.6 152.0 168.0 160.3
 [6,]  85.7  98.7 117.8 116.2 116.2  98.7 123.1 135.3 132.6 142.2 139.3 135.2
 [7,] 104.6 114.5 120.3 118.6 121.4 145.8 130.0 149.3 139.6 137.2 138.6 148.8
 [8,] 105.1 113.8 121.0 130.7 127.8 151.7 150.1 143.4 147.0 152.6 153.4 151.0
 [9,] 117.3 133.1 132.3 129.3 143.6 129.4 169.4 142.2 166.6 166.8 138.9 148.2
[10,] 142.5 143.4 142.9 144.4 157.6 174.1 179.7 188.4 157.0 165.6 172.1 182.2
[11,] 140.0 137.3 147.4 163.2 166.2 197.0 182.1 166.2 180.4 198.6 198.4 189.2
[12,] 159.8 165.2 175.9 179.4 182.3 193.9 194.3 199.2 210.2 201.5 217.8 183.1
      [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36]
 [1,] 170.0 203.6 159.4 141.6 151.5 166.5 161.2 177.2 154.1 153.3 172.0 164.4
 [2,] 158.4 175.2 161.1 148.1 158.1 151.3 155.5 127.4 159.3 144.3 150.6 148.1
 [3,] 176.1 168.7 172.1 184.9 143.0 146.2 141.9 177.1 160.4 169.6 163.3 152.0
 [4,] 156.2 155.9 158.4 132.5 151.2 148.3 164.6 154.4 151.9 143.7 153.7 144.1
 [5,] 153.2 147.3 114.6 137.3 147.6 144.7 136.2 135.2 148.4 160.1 152.9 155.0
 [6,] 117.9 137.0 159.6 135.5 130.7 123.6 126.8 126.4 139.6 135.6 135.5 124.5
 [7,] 149.8 141.1 159.7 121.7 137.5 151.6 152.5 147.3 148.2 141.8 148.5 153.0
 [8,] 156.6 167.4 159.4 166.1 146.1 133.9 126.6 140.6 153.5 159.9 148.4 146.0
 [9,] 166.7 160.2 160.7 146.8 133.6 137.4 150.1 152.3 145.1 145.7 133.6 138.0
[10,] 156.8 191.9 165.5 162.8 167.9 181.6 186.3 151.2 183.7 183.5 194.1 190.0
[11,] 158.6 174.4 205.0 186.8 181.9 182.0 147.5 172.2 210.5 198.2 208.6 192.0
[12,] 210.8 208.2 205.2 185.5 202.0 190.0 200.4 215.3 203.3 186.8 197.3 192.0
      [,37] [,38] [,39]
 [1,]   147   139   151
 [2,]   133   143   134
 [3,]   163   150   164
 [4,]   150   154   126
 [5,]   129   137   131
 [6,]   131   129   125
 [7,]   145   128   127
 [8,]   137   140   143
 [9,]   138   143   143
[10,]   168   151   160
[11,]   176   177   190
[12,]   188   184   182
> 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]  86.04167  87.20000  87.92500  87.70000  90.36667  93.64167  95.36667
 [8]  99.11667 104.65000 109.21667 111.15000 116.55000 123.43333 126.83333
[15] 131.96667 137.08333 141.23333 153.14167 159.57500 161.68333 161.97500
[22] 163.39167 166.52500 162.35000 160.92500 169.24167 165.05833 154.13333
[29] 154.25833 154.75833 154.13333 156.38333 163.16667 160.20833 163.20833
[36] 158.25833 150.41667 147.91667 148.00000
> arr.sd
 [1] 14.26480 14.24819 12.66822 13.24043 12.81152 14.75087 13.76249 16.09460
 [9] 14.31303 15.63410 17.26481 14.26595 19.97495 17.22315 17.48050 19.50002
[17] 20.33167 26.82589 20.93571 18.67968 23.04317 19.49799 24.16057 17.60560
[25] 21.18731 23.06140 23.36285 22.59048 20.80513 20.86256 22.10727 25.49638
[33] 23.20225 20.24744 24.66118 22.16391 19.18550 17.22291 21.98760
> arr.range
 [1] 42.3 46.6 43.4 47.2 39.5 44.2 45.9 54.9 48.4 46.5 53.1 50.9 74.1 66.5 66.5
[16] 63.2 66.1 98.3 71.2 63.9 77.6 64.3 79.2 54.0 92.9 71.2 90.6 65.1 71.3 66.4
[31] 73.8 88.9 70.9 62.6 75.0 67.5 59.0 56.0 65.0
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
     3.2318       0.1167  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -1.0125         0.8064  

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

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

Coefficients:
(Intercept)     arr.mean  
     9.6807       0.3961  

> postscript(file="/var/www/html/rcomp/tmp/1qxc71275892540.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/2i7ba1275892540.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/3lprg1275892540.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4pq841275892540.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/5sq7s1275892540.tab") 
> 
> try(system("convert tmp/1qxc71275892540.ps tmp/1qxc71275892540.png",intern=TRUE))
character(0)
> try(system("convert tmp/2i7ba1275892540.ps tmp/2i7ba1275892540.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.566   0.287   0.721