R version 2.15.2 (2012-10-26) -- "Trick or Treat"
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(1,88,2,94,2,90,2,73,1,68,2,80,2,86,3,86,3,91,1,79,3,96,2,92,3,72,2,96,1,70,2,86,2,87,3,88,2,79,1,90,2,95,2,85,2,90,3,115,3,84,2,79,1,94,2,97,2,86,3,111,2,87,3,98,3,87,1,68,1,88,3,82,3,111,2,75,1,94,1,95,1,80,2,95,2,68,1,94,1,88,3,84,1,101,2,98,3,78,2,109,2,102,1,81,3,97,3,75,2,97,1,101,3,101,2,95,2,95,2,95,1,90,2,107,3,92,2,86,1,70,3,95,1,96,2,91,3,87,1,92,3,97,2,102,1,91,2,68,1,88,2,97,2,90,3,101,3,94,3,101,3,109,2,100,2,103,2,94,3,97,1,85,1,75,2,77,1,87,3,78,2,108,2,97,2,106,2,107,2,95,3,107,2,115,2,101,3,85,3,90,3,115,2,95,2,97,1,112,3,97,2,77,2,90,2,94,2,103,2,77,1,98,2,90,2,111,1,77,1,88,2,75,3,92,1,78,3,106,1,80,2,87,2,92,1,86,3,85,2,90,3,101,2,94,2,86,3,86,2,90,3,75,2,86,1,91,2,97,1,91,1,70,1,98,1,96,2,95,2,100,2,95,1,97,3,97,3,92,3,115,2,88,1,87,2,100,3,98,2,102,1,96),dim=c(2,151),dimnames=list(c('MWARM30','WISCRY7V


'),1:151))
>  y <- array(NA,dim=c(2,151),dimnames=list(c('MWARM30','WISCRY7V


'),1:151))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par3 = 'TRUE'
> par2 = '2'
> par1 = '1'
> ylab = 'Y Variable Name'
> xlab = 'X Variable Name'
> main = 'Title Goes Here'
> par3 <- 'TRUE'
> par2 <- '2'
> par1 <- '1'
> 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] "MWARM30"
> (V2<-dimnames(y)[[1]][cat2])
[1] "WISCRY7V\r\r\r"
> 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, data = xdf)

Coefficients:
 (Intercept)  Treatment101  Treatment102  Treatment103  Treatment106  
   2.000e+00     2.857e-01     2.241e-16     2.005e-16     5.000e-01  
Treatment107  Treatment108  Treatment109  Treatment111  Treatment112  
   3.333e-01     1.915e-16     5.000e-01     6.667e-01    -1.000e+00  
Treatment115   Treatment68   Treatment70   Treatment72   Treatment73  
   7.500e-01    -5.000e-01    -1.000e+00     1.000e+00     2.777e-16  
 Treatment75   Treatment77   Treatment78   Treatment79   Treatment80  
   2.000e-01    -2.500e-01     3.333e-01    -3.333e-01    -6.667e-01  
 Treatment81   Treatment82   Treatment84   Treatment85   Treatment86  
  -1.000e+00     1.000e+00     1.000e+00     2.500e-01     1.111e-01  
 Treatment87   Treatment88   Treatment90   Treatment91   Treatment92  
   2.180e-16    -5.714e-01    -1.000e-01    -4.000e-01     3.333e-01  
 Treatment94   Treatment95   Treatment96   Treatment97   Treatment98  
  -2.500e-01     1.899e-16    -4.000e-01     3.333e-01     3.432e-16  

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

Terms:
                Treatment Residuals
Sum of Squares   24.75843  57.21508
Deg. of Freedom        34       116

Residual standard error: 0.7023058 
Estimated effects may be unbalanced
> (anova.xdf<-anova(lmxdf) )
Analysis of Variance Table

Response: Response
           Df Sum Sq Mean Sq F value Pr(>F)  
Treatment  34 24.758 0.72819  1.4764 0.0661 .
Residuals 116 57.215 0.49323                 
---
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/1m58i1352163959.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/28f4a1352163959.tab") 
> postscript(file="/var/fisher/rcomp/tmp/3sokl1352163959.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
Warning messages:
1: In title(xlab = "WISCRY7V\r\r\r", ylab = "MWARM30") :
  font width unknown for character 0xd
2: In title(xlab = "WISCRY7V\r\r\r", ylab = "MWARM30") :
  font width unknown for character 0xd
3: In title(xlab = "WISCRY7V\r\r\r", ylab = "MWARM30") :
  font width unknown for character 0xd
> dev.off()
null device 
          1 
> if(intercept==TRUE){
+ 'Tukey Plot'
+ thsd<-TukeyHSD(aov.xdf)
+ postscript(file="/var/fisher/rcomp/tmp/4dkdd1352163959.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
+ plot(thsd)
+ dev.off()
+ }
null device 
          1 
> 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/5tdt21352163959.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/66rab1352163959.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/7g47s1352163959.tab") 
> 
> try(system("convert tmp/3sokl1352163959.ps tmp/3sokl1352163959.png",intern=TRUE))
character(0)
> try(system("convert tmp/4dkdd1352163959.ps tmp/4dkdd1352163959.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  9.837   0.380  10.203