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(15.5,15.1,11.7,16.3,16.7,15,14.9,14.6,15.3,17.9,16.4,15.4,17.9,15.9,13.9,17.8,17.9,17.4,16.7,16,16.6,19.1,17.8,17.2,18.6,16.3,15.1,19.2,17.7,19.1,18,17.5,17.8,21.1,17.2,19.4,19.8,17.6,16.2,19.5,19.9,20,17.3,18.9,18.6,21.4,18.6,19.8,20.8,19.6,17.7,19.8,22.2,20.7,17.9,20.9,21.2,21.4,23,21.3,23.9,22.4,18.3,22.8,22.3,17.8,16.4,16,16.4,17.7,16.6,16.2,18.3)
> #'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!)
> n <- length(x)
> c <- array(NA,dim=c(401))
> l <- array(NA,dim=c(401))
> mx <- 0
> mxli <- -999
> for (i in 1:401)
+ {
+ l[i] <- (i-201)/100
+ if (l[i] != 0)
+ {
+ x1 <- (x^l[i] - 1) / l[i]
+ } else {
+ x1 <- log(x)
+ }
+ c[i] <- cor(qnorm(ppoints(x), mean=0, sd=1),x1)
+ if (mx < c[i])
+ {
+ mx <- c[i]
+ mxli <- l[i]
+ }
+ }
> c
  [1] 0.5327153 0.5327791 0.5328422 0.5329044 0.5329658 0.5330263 0.5330860
  [8] 0.5331449 0.5332029 0.5332602 0.5333165 0.5333721 0.5334268 0.5334807
 [15] 0.5335338 0.5335861 0.5336375 0.5336881 0.5337379 0.5337869 0.5338351
 [22] 0.5338824 0.5339290 0.5339747 0.5340196 0.5340637 0.5341070 0.5341495
 [29] 0.5341912 0.5342321 0.5342722 0.5343115 0.5343500 0.5343877 0.5344246
 [36] 0.5344607 0.5344960 0.5345306 0.5345643 0.5345972 0.5346294 0.5346608
 [43] 0.5346914 0.5347212 0.5347502 0.5347785 0.5348059 0.5348327 0.5348586
 [50] 0.5348837 0.5349081 0.5349318 0.5349546 0.5349767 0.5349980 0.5350186
 [57] 0.5350384 0.5350574 0.5350757 0.5350933 0.5351101 0.5351261 0.5351414
 [64] 0.5351559 0.5351697 0.5351827 0.5351950 0.5352066 0.5352174 0.5352275
 [71] 0.5352368 0.5352455 0.5352533 0.5352605 0.5352669 0.5352726 0.5352776
 [78] 0.5352818 0.5352854 0.5352882 0.5352903 0.5352916 0.5352923 0.5352922
 [85] 0.5352915 0.5352900 0.5352878 0.5352849 0.5352814 0.5352771 0.5352721
 [92] 0.5352664 0.5352600 0.5352530 0.5352452 0.5352367 0.5352276 0.5352178
 [99] 0.5352073 0.5351961 0.5351842 0.5351717 0.5351584 0.5351445 0.5351300
[106] 0.5351147 0.5350988 0.5350822 0.5350650 0.5350471 0.5350285 0.5350093
[113] 0.5349894 0.5349689 0.5349477 0.5349259 0.5349034 0.5348802 0.5348564
[120] 0.5348320 0.5348069 0.5347812 0.5347549 0.5347279 0.5347003 0.5346721
[127] 0.5346432 0.5346137 0.5345836 0.5345528 0.5345214 0.5344894 0.5344568
[134] 0.5344236 0.5343898 0.5343553 0.5343203 0.5342846 0.5342483 0.5342114
[141] 0.5341740 0.5341359 0.5340972 0.5340579 0.5340181 0.5339776 0.5339365
[148] 0.5338949 0.5338527 0.5338099 0.5337665 0.5337225 0.5336780 0.5336329
[155] 0.5335872 0.5335409 0.5334941 0.5334466 0.5333987 0.5333501 0.5333010
[162] 0.5332514 0.5332012 0.5331504 0.5330991 0.5330472 0.5329947 0.5329418
[169] 0.5328882 0.5328342 0.5327796 0.5327244 0.5326687 0.5326125 0.5325557
[176] 0.5324984 0.5324406 0.5323823 0.5323234 0.5322640 0.5322040 0.5321436
[183] 0.5320826 0.5320211 0.5319592 0.5318966 0.5318336 0.5317701 0.5317060
[190] 0.5316415 0.5315765 0.5315109 0.5314449 0.5313783 0.5313113 0.5312437
[197] 0.5311757 0.5311072 0.5310382 0.5309687 0.5308987 0.5308283 0.5307574
[204] 0.5306859 0.5306141 0.5305417 0.5304689 0.5303956 0.5303218 0.5302475
[211] 0.5301728 0.5300977 0.5300220 0.5299459 0.5298694 0.5297924 0.5297149
[218] 0.5296370 0.5295587 0.5294799 0.5294006 0.5293209 0.5292408 0.5291602
[225] 0.5290792 0.5289977 0.5289158 0.5288335 0.5287508 0.5286676 0.5285840
[232] 0.5284999 0.5284155 0.5283306 0.5282453 0.5281596 0.5280734 0.5279869
[239] 0.5278999 0.5278125 0.5277247 0.5276365 0.5275479 0.5274589 0.5273695
[246] 0.5272797 0.5271895 0.5270989 0.5270079 0.5269165 0.5268247 0.5267326
[253] 0.5266400 0.5265470 0.5264537 0.5263600 0.5262659 0.5261714 0.5260766
[260] 0.5259813 0.5258857 0.5257897 0.5256934 0.5255967 0.5254996 0.5254021
[267] 0.5253043 0.5252061 0.5251076 0.5250087 0.5249094 0.5248098 0.5247098
[274] 0.5246095 0.5245088 0.5244078 0.5243064 0.5242047 0.5241027 0.5240003
[281] 0.5238975 0.5237944 0.5236910 0.5235873 0.5234832 0.5233788 0.5232740
[288] 0.5231689 0.5230635 0.5229578 0.5228517 0.5227453 0.5226386 0.5225316
[295] 0.5224242 0.5223166 0.5222086 0.5221003 0.5219917 0.5218828 0.5217735
[302] 0.5216640 0.5215542 0.5214440 0.5213336 0.5212228 0.5211118 0.5210004
[309] 0.5208888 0.5207769 0.5206646 0.5205521 0.5204393 0.5203262 0.5202128
[316] 0.5200991 0.5199851 0.5198709 0.5197563 0.5196415 0.5195264 0.5194111
[323] 0.5192954 0.5191795 0.5190633 0.5189468 0.5188301 0.5187131 0.5185958
[330] 0.5184783 0.5183605 0.5182424 0.5181241 0.5180055 0.5178866 0.5177675
[337] 0.5176482 0.5175285 0.5174087 0.5172885 0.5171682 0.5170475 0.5169266
[344] 0.5168055 0.5166842 0.5165625 0.5164407 0.5163186 0.5161963 0.5160737
[351] 0.5159509 0.5158278 0.5157045 0.5155810 0.5154573 0.5153333 0.5152091
[358] 0.5150846 0.5149600 0.5148351 0.5147099 0.5145846 0.5144590 0.5143332
[365] 0.5142072 0.5140810 0.5139546 0.5138279 0.5137010 0.5135740 0.5134467
[372] 0.5133192 0.5131914 0.5130635 0.5129354 0.5128070 0.5126785 0.5125498
[379] 0.5124208 0.5122917 0.5121623 0.5120328 0.5119030 0.5117731 0.5116429
[386] 0.5115126 0.5113821 0.5112513 0.5111204 0.5109893 0.5108580 0.5107266
[393] 0.5105949 0.5104631 0.5103310 0.5101988 0.5100664 0.5099338 0.5098011
[400] 0.5096682 0.5095350
> mx
[1] 0.5352923
> mxli
[1] -1.18
> if (mxli != 0)
+ {
+ x1 <- (x^mxli - 1) / mxli
+ } else {
+ x1 <- log(x)
+ }
> postscript(file="/var/www/html/rcomp/tmp/1ud811261053500.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(l,c,main='Box-Cox Normality Plot',xlab='Lambda',ylab='correlation')
> mtext(paste('Optimal Lambda =',mxli))
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2wywl1261053500.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(x,main='Histogram of Original Data',xlab='X',ylab='frequency')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3o2cp1261053500.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(x1,main='Histogram of Transformed Data',xlab='X',ylab='frequency')
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4ga4u1261053500.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> mtext('Original Data')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/50lvt1261053500.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x1)
> qqline(x1)
> grid()
> mtext('Transformed Data')
> 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,'Box-Cox Normality Plot',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'# observations x',header=TRUE)
> a<-table.element(a,n)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'maximum correlation',header=TRUE)
> a<-table.element(a,mx)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'optimal lambda',header=TRUE)
> a<-table.element(a,mxli)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/659nw1261053500.tab") 
> 
> try(system("convert tmp/1ud811261053500.ps tmp/1ud811261053500.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wywl1261053500.ps tmp/2wywl1261053500.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o2cp1261053500.ps tmp/3o2cp1261053500.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ga4u1261053500.ps tmp/4ga4u1261053500.png",intern=TRUE))
character(0)
> try(system("convert tmp/50lvt1261053500.ps tmp/50lvt1261053500.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.114   0.801   1.348