R version 2.7.2 (2008-08-25)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(119.5,125,145,105.3,116.9,120.1,88.9,78.4,114.6,113.3,117,99.6,99.4,101.9,115.2,108.5,113.8,121,92.2,90.2,101.5,126.6,93.9,89.8,93.4,101.5,110.4,105.9,108.4,113.9,86.1,69.4,101.2,100.5,98,106.6,90.1,96.9,125.9,112,100,123.9,79.8,83.4,113.6,112.9,104,109.9,99,106.3,128.9,111.1,102.9,130,87,87.5,117.6,103.4,110.8,112.6,102.5,112.4,135.6,105.1,127.7,137,91,90.5,122.4,123.3,124.3,120,118.1,119,142.7,123.6,129.6,146.9,108.7,99.4)
> par1 = '36'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa P., (2007), Mean Plot (v1.0.1) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_meanplot.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 80
> (np <- floor(n / par1))
[1] 2
> arr <- array(NA,dim=c(par1,np+1))
> ari <- array(0,dim=par1)
> j <- 0
> for (i in 1:n)
+ {
+ j = j + 1
+ ari[j] = ari[j] + 1
+ arr[j,ari[j]] <- x[i]
+ if (j == par1) j = 0
+ }
> ari
 [1] 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
> arr
       [,1]  [,2]  [,3]
 [1,] 119.5  90.1 118.1
 [2,] 125.0  96.9 119.0
 [3,] 145.0 125.9 142.7
 [4,] 105.3 112.0 123.6
 [5,] 116.9 100.0 129.6
 [6,] 120.1 123.9 146.9
 [7,]  88.9  79.8 108.7
 [8,]  78.4  83.4  99.4
 [9,] 114.6 113.6    NA
[10,] 113.3 112.9    NA
[11,] 117.0 104.0    NA
[12,]  99.6 109.9    NA
[13,]  99.4  99.0    NA
[14,] 101.9 106.3    NA
[15,] 115.2 128.9    NA
[16,] 108.5 111.1    NA
[17,] 113.8 102.9    NA
[18,] 121.0 130.0    NA
[19,]  92.2  87.0    NA
[20,]  90.2  87.5    NA
[21,] 101.5 117.6    NA
[22,] 126.6 103.4    NA
[23,]  93.9 110.8    NA
[24,]  89.8 112.6    NA
[25,]  93.4 102.5    NA
[26,] 101.5 112.4    NA
[27,] 110.4 135.6    NA
[28,] 105.9 105.1    NA
[29,] 108.4 127.7    NA
[30,] 113.9 137.0    NA
[31,]  86.1  91.0    NA
[32,]  69.4  90.5    NA
[33,] 101.2 122.4    NA
[34,] 100.5 123.3    NA
[35,]  98.0 124.3    NA
[36,] 106.6 120.0    NA
> arr.mean <- array(NA,dim=par1)
> arr.median <- array(NA,dim=par1)
> arr.midrange <- array(NA,dim=par1)
> for (j in 1:par1)
+ {
+ arr.mean[j] <- mean(arr[j,],na.rm=TRUE)
+ arr.median[j] <- median(arr[j,],na.rm=TRUE)
+ arr.midrange[j] <- (quantile(arr[j,],0.75,na.rm=TRUE) + quantile(arr[j,],0.25,na.rm=TRUE)) / 2
+ }
> overall.mean <- mean(x)
> overall.median <- median(x)
> overall.midrange <- (quantile(x,0.75) + quantile(x,0.25)) / 2
> postscript(file="/var/www/html/rcomp/tmp/1duvu1225733206.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,type='b',ylab='mean',main='Mean Plot',xlab='Periodic Index')
> mtext(paste('#blocks = ',np))
> abline(overall.mean,0)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/27gac1225733206.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.median,type='b',ylab='median',main='Median Plot',xlab='Periodic Index')
> mtext(paste('#blocks = ',np))
> abline(overall.median,0)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3ag6n1225733206.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.midrange,type='b',ylab='midrange',main='Midrange Plot',xlab='Periodic Index')
> mtext(paste('#blocks = ',np))
> abline(overall.midrange,0)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4nixy1225733206.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> z <- data.frame(t(arr))
> names(z) <- c(1:par1)
> (boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Periodic Subseries'))
$stats
      [,1]   [,2]   [,3]   [,4]   [,5]  [,6]   [,7] [,8]  [,9] [,10] [,11]
[1,]  90.1  96.90 125.90 105.30 100.00 120.1  79.80 78.4 113.6 112.9 104.0
[2,] 104.1 107.95 134.30 108.65 108.45 122.0  84.35 80.9 113.6 112.9 104.0
[3,] 118.1 119.00 142.70 112.00 116.90 123.9  88.90 83.4 114.1 113.1 110.5
[4,] 118.8 122.00 143.85 117.80 123.25 135.4  98.80 91.4 114.6 113.3 117.0
[5,] 119.5 125.00 145.00 123.60 129.60 146.9 108.70 99.4 114.6 113.3 117.0
      [,12] [,13] [,14]  [,15] [,16]  [,17] [,18] [,19] [,20]  [,21] [,22]
[1,]  99.60  99.0 101.9 115.20 108.5 102.90 121.0  87.0 87.50 101.50 103.4
[2,]  99.60  99.0 101.9 115.20 108.5 102.90 121.0  87.0 87.50 101.50 103.4
[3,] 104.75  99.2 104.1 122.05 109.8 108.35 125.5  89.6 88.85 109.55 115.0
[4,] 109.90  99.4 106.3 128.90 111.1 113.80 130.0  92.2 90.20 117.60 126.6
[5,] 109.90  99.4 106.3 128.90 111.1 113.80 130.0  92.2 90.20 117.60 126.6
      [,23] [,24]  [,25]  [,26] [,27] [,28]  [,29]  [,30] [,31] [,32] [,33]
[1,]  93.90  89.8  93.40 101.50 110.4 105.1 108.40 113.90 86.10 69.40 101.2
[2,]  93.90  89.8  93.40 101.50 110.4 105.1 108.40 113.90 86.10 69.40 101.2
[3,] 102.35 101.2  97.95 106.95 123.0 105.5 118.05 125.45 88.55 79.95 111.8
[4,] 110.80 112.6 102.50 112.40 135.6 105.9 127.70 137.00 91.00 90.50 122.4
[5,] 110.80 112.6 102.50 112.40 135.6 105.9 127.70 137.00 91.00 90.50 122.4
     [,34]  [,35] [,36]
[1,] 100.5  98.00 106.6
[2,] 100.5  98.00 106.6
[3,] 111.9 111.15 113.3
[4,] 123.3 124.30 120.0
[5,] 123.3 124.30 120.0

$n
 [1] 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

$conf
         [,1]     [,2]     [,3]     [,4]     [,5]     [,6]      [,7]     [,8]
[1,] 104.6905 106.1834 133.9884 103.6532 103.3992 111.6763  75.71852 73.82176
[2,] 131.5095 131.8166 151.4116 120.3468 130.4008 136.1237 102.08148 92.97824
         [,9]    [,10]     [,11]     [,12]   [,13]    [,14]    [,15]    [,16]
[1,] 112.9828 112.6531  95.97603  93.24254 98.7531  99.1842 106.7440 106.8952
[2,] 115.2172 113.5469 125.02397 116.25746 99.6469 109.0158 137.3560 112.7048
        [,17]    [,18]    [,19]    [,20]     [,21]    [,22]     [,23]     [,24]
[1,]  96.1722 115.4449 83.79041 85.83348  91.56262  89.0803  83.46883  75.72719
[2,] 120.5278 135.5551 95.40959 91.86652 127.53738 140.9197 121.23117 126.67281
         [,25]    [,26]     [,27]    [,28]     [,29]     [,30]    [,31]
[1,]  87.78322  94.7722  94.84584 104.6062  96.48749  99.64202 83.07558
[2,] 108.11678 119.1278 151.15416 106.3938 139.61251 151.25798 94.02442
         [,32]     [,33]     [,34]     [,35]     [,36]
[1,]  56.37647  88.11475  86.42719  81.76688  98.32914
[2,] 103.52353 135.48525 137.37281 140.53312 128.27086

$out
numeric(0)

$group
numeric(0)

$names
 [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10" "11" "12" "13" "14" "15"
[16] "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30"
[31] "31" "32" "33" "34" "35" "36"

Warning message:
In bxp(list(stats = c(90.1, 104.1, 118.1, 118.8, 119.5, 96.9, 107.95,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/5he471225733206.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> z <- data.frame(arr)
> names(z) <- c(1:np)
> (boxplot(z,notch=TRUE,col='grey',xlab='Block Index',ylab='Value',main='Notched Box Plots - Sequential Blocks'))
$stats
       [,1]   [,2]   [,3]
[1,]  69.40  79.80  99.40
[2,]  95.95  99.50 113.40
[3,] 105.60 110.95 121.30
[4,] 114.90 122.85 136.15
[5,] 126.60 137.00 146.90

$n
[1] 36 36  8

$conf
         [,1]     [,2]     [,3]
[1,] 100.6098 104.8012 108.5915
[2,] 110.5902 117.0988 134.0085

$out
[1] 145

$group
[1] 1

$names
[1] "1" "2" NA 

Warning message:
In bxp(list(stats = c(69.4, 95.95, 105.6, 114.9, 126.6, 79.8, 99.5,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6w5y31225733206.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> z <- data.frame(cbind(arr.mean,arr.median,arr.midrange))
> names(z) <- list('mean','median','midrange')
> (boxplot(z,notch=TRUE,col='grey',ylab='Overall Central Tendency',main='Notched Box Plots'))
$stats
          [,1]    [,2]     [,3]
[1,]  87.06667  79.950  86.1500
[2,] 101.77500 101.775 101.7750
[3,] 110.15000 110.825 110.8250
[4,] 114.55000 117.475 114.9875
[5,] 130.30000 125.500 128.7000

$n
[1] 36 36 36

$conf
         [,1]     [,2]     [,3]
[1,] 106.7859 106.6907 107.3457
[2,] 113.5141 114.9593 114.3043

$out
[1] 137.8667  79.9500 142.7000 139.0750  79.9500

$group
[1] 1 1 2 3 3

$names
[1] "mean"     "median"   "midrange"

> dev.off()
null device 
          1 
> system("convert tmp/1duvu1225733206.ps tmp/1duvu1225733206.png")
> system("convert tmp/27gac1225733206.ps tmp/27gac1225733206.png")
> system("convert tmp/3ag6n1225733206.ps tmp/3ag6n1225733206.png")
> system("convert tmp/4nixy1225733206.ps tmp/4nixy1225733206.png")
> system("convert tmp/5he471225733206.ps tmp/5he471225733206.png")
> system("convert tmp/6w5y31225733206.ps tmp/6w5y31225733206.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.376   0.856   2.048