R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- array(list(3,36,1,36,3,56,3,48,3,32,1,44,2,39,3,34,3,41,2,50,1,39,1,62,3,52,3,37,3,50,1,41,3,55,3,41,3,56,2,39,2,52,1,46,1,44,3,48,3,41,1,50,1,50,3,44,1,52,2,54,3,44,2,52,2,37,3,52,1,50,3,36,3,50,1,52,2,55,1,31,1,36,2,49,1,42,1,37,3,41,2,30,2,52,1,30,1,41,1,44,1,66,2,48,3,43,3,57,3,46,3,54,2,48,2,48,2,52,3,62,3,58,2,58,2,62,2,48,3,46,2,34,3,66,3,52,2,55,2,55,3,57,3,56,2,55,1,56,2,54,2,55,2,46,2,52,3,32,2,44,3,46,1,59,3,46,3,46,1,54,1,66,2,56,1,59,3,57,1,52,3,48,2,44,3,41,1,50,1,48,2,48,3,59,1,34,3,46,1,54,2,55,2,54,3,59,3,44,1,54,3,52,3,66,3,44,2,57,3,39,3,60,3,45,3,41,1,50,3,39,1,43,3,48,3,37,3,58,2,46,3,43,2,44,3,34,2,30,2,50,2,39,3,37,3,55,1,48,1,41,3,39,3,36,2,43,1,50,3,55,3,43,3,60,2,48,1,30,3,43,3,39,3,52,2,39,3,39,2,56,3,59,3,46,2,57,3,50,3,54,3,50,3,60,1,59,3,41,2,48,3,59,3,60,1,56,1,56,3,51),dim=c(2,160),dimnames=list(c('age','verbal'),1:160))
>  y <- array(NA,dim=c(2,160),dimnames=list(c('age','verbal'),1:160))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par3 = 'FALSE'
> par2 = '2'
> par1 = '1'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> par3 <- 'FALSE'
> par2 <- '2'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: aston2
> #To cite this work: Ian E. Holliday, 2012, One-Way-Between-Groups ANOVA (v1.0.4) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_One%20Factor%20ANOVA.wasp/
> #Source of accompanying publication: 
> #
> cat1 <- as.numeric(par1) #
> cat2<- as.numeric(par2) #
> intercept<-as.logical(par3)
> x <- t(x)
> x1<-as.numeric(x[,cat1])
> f1<-as.character(x[,cat2])
> xdf<-data.frame(x1,f1)
> (V1<-dimnames(y)[[1]][cat1])
[1] "age"
> (V2<-dimnames(y)[[1]][cat2])
[1] "verbal"
> names(xdf)<-c('Response', 'Treatment')
> if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )

Call:
lm(formula = Response ~ Treatment - 1, data = xdf)

Coefficients:
Treatment30  Treatment31  Treatment32  Treatment34  Treatment36  Treatment37  
      1.500        1.000        3.000        2.250        2.200        2.400  
Treatment39  Treatment41  Treatment42  Treatment43  Treatment44  Treatment45  
      2.400        2.400        1.000        2.500        2.100        3.000  
Treatment46  Treatment48  Treatment49  Treatment50  Treatment51  Treatment52  
      2.600        2.154        2.000        1.833        3.000        2.154  
Treatment54  Treatment55  Treatment56  Treatment57  Treatment58  Treatment59  
      1.875        2.333        2.000        2.600        2.667        2.143  
Treatment60  Treatment62  Treatment66  
      3.000        2.000        2.000  

> (aov.xdf<-aov(lmxdf) )
Call:
   aov(formula = lmxdf)

Terms:
                Treatment Residuals
Sum of Squares   809.9999   90.0001
Deg. of Freedom        27       133

Residual standard error: 0.8226132 
Estimated effects are balanced
> (anova.xdf<-anova(lmxdf) )
Analysis of Variance Table

Response: Response
           Df Sum Sq Mean Sq F value    Pr(>F)    
Treatment  27    810 30.0000  44.333 < 2.2e-16 ***
Residuals 133     90  0.6767                      
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'means',,TRUE)
> for(i in 1:length(lmxdf$coefficients)){
+ a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
+ }
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/1n6361351777485.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ',,TRUE)
> a<-table.element(a, 'Df',,FALSE)
> a<-table.element(a, 'Sum Sq',,FALSE)
> a<-table.element(a, 'Mean Sq',,FALSE)
> a<-table.element(a, 'F value',,FALSE)
> a<-table.element(a, 'Pr(>F)',,FALSE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, V2,,TRUE)
> a<-table.element(a, anova.xdf$Df[1],,FALSE)
> a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residuals',,TRUE)
> a<-table.element(a, anova.xdf$Df[2],,FALSE)
> a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
> a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.element(a, ' ',,FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/29vuc1351777485.tab") 
> postscript(file="/var/fisher/rcomp/tmp/37q0n1351777485.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
> dev.off()
null device 
          1 
> if(intercept==TRUE){
+ 'Tukey Plot'
+ thsd<-TukeyHSD(aov.xdf)
+ postscript(file="/var/fisher/rcomp/tmp/4y5f91351777485.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ plot(thsd)
+ dev.off()
+ }
> if(intercept==TRUE){
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a, ' ', 1, TRUE)
+ for(i in 1:4){
+ a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
+ }
+ a<-table.row.end(a)
+ for(i in 1:length(rownames(thsd[[1]]))){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
+ for(j in 1:4){
+ a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
+ }
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/5dcjp1351777485.tab") 
+ }
> if(intercept==FALSE){
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'TukeyHSD Message', 1,TRUE)
+ a<-table.row.end(a)
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/6mlan1351777485.tab") 
+ }
> library(car)
Loading required package: MASS
Loading required package: nnet
> lt.lmxdf<-leveneTest(lmxdf)
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,' ', 1, TRUE)
> for (i in 1:3){
+ a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
+ }
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Group', 1, TRUE)
> for (i in 1:3){
+ a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
+ }
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,' ', 1, TRUE)
> a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
> a<-table.element(a,' ', 1, FALSE)
> a<-table.element(a,' ', 1, FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/7zbcc1351777485.tab") 
> 
> try(system("convert tmp/37q0n1351777485.ps tmp/37q0n1351777485.png",intern=TRUE))
character(0)
> try(system("convert tmp/4y5f91351777485.ps tmp/4y5f91351777485.png",intern=TRUE))
convert: unable to open image `tmp/4y5f91351777485.ps':  @ error/blob.c/OpenBlob/2587.
convert: missing an image filename `tmp/4y5f91351777485.png' @ error/convert.c/ConvertImageCommand/3011.
character(0)
attr(,"status")
[1] 1
Warning message:
running command 'convert tmp/4y5f91351777485.ps tmp/4y5f91351777485.png' had status 1 
> 
> 
> proc.time()
   user  system elapsed 
  1.037   0.245   1.264