R version 2.12.1 (2010-12-16)
Copyright (C) 2010 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(1.6,-41,1.8,55,5.2,30,4.1,0,0.4,17,2.7,-61,2.4,27,2.6,1,2.4,-67,7.2,80,3.7,-70,8.4,41,1.5,-37,8.0,0,0.0,7,7.1,-50,2.8,74,8.2,79,2.3,56,5.0,18,5.9,4,6.2,15,3.6,69,1.6,-6,3.2,32,2.6,57,1.6,59,5.8,68,2.8,-39,1.2,8,-1.5,-349,7.8,169,2.5,51,9.6,43,7.4,58),dim=c(2,35),dimnames=list(c('X','Y'),1:35))
>  y <- array(NA,dim=c(2,35),dimnames=list(c('X','Y'),1:35))
>  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 = '1'
> par1 = '2'
> ylab = 'Triglyceride Difference'
> xlab = 'Weight Loss Reduction'
> main = 'Title Goes Here'
> cat1 <- as.numeric(par1) #
> cat2<- as.numeric(par2) #
> intercept<-as.logical(par3)
> x <- t(x)
> xdf<-data.frame(t(y))
> (V1<-dimnames(y)[[1]][cat1])
[1] "Y"
> (V2<-dimnames(y)[[1]][cat2])
[1] "X"
> xdf <- data.frame(xdf[[cat1]], xdf[[cat2]])
> names(xdf)<-c('Y', 'X')
> if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) )

Call:
lm(formula = Y ~ X, data = xdf)

Coefficients:
(Intercept)            X  
     -41.79        13.51  

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

Terms:
                        X Residuals
Sum of Squares   47340.68 172221.49
Deg. of Freedom         1        33

Residual standard error: 72.24149 
Estimated effects may be unbalanced
> (anova.xdf<-anova(lmxdf) )
Analysis of Variance Table

Response: Y
          Df Sum Sq Mean Sq F value   Pr(>F)   
X          1  47341   47341  9.0711 0.004954 **
Residuals 33 172221    5219                    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
> 
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
> 
> a<-table.start()
> nc <- ncol(sumlmxdf$'coefficients')
> nr <- nrow(sumlmxdf$'coefficients')
> a<-table.row.start(a)
> a<-table.element(a,'Linear Regression Model', nc+1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, lmxdf$call['formula'],nc+1)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'coefficients:',1,TRUE)
> a<-table.element(a, ' ',nc,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, ' ',1,TRUE)
> for(i in 1 : nc){
+ a<-table.element(a, dimnames(sumlmxdf$'coefficients')[[2]][i],1,TRUE)
+ }#end header
> a<-table.row.end(a)
> for(i in 1: nr){
+ a<-table.element(a,dimnames(sumlmxdf$'coefficients')[[1]][i] ,1,TRUE)
+ for(j in 1 : nc){
+ a<-table.element(a, round(sumlmxdf$coefficients[i, j], digits=3), 1 ,FALSE)
+ }# end cols
+ a<-table.row.end(a)
+ } #end rows
> a<-table.row.start(a)
> a<-table.element(a, '- - - ',1,TRUE)
> a<-table.element(a, ' ',nc,FALSE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Std. Err. ',1,TRUE)
> a<-table.element(a, paste(round(sumlmxdf$'sigma', digits=3), ' on ', sumlmxdf$'df'[2], 'df') ,nc, FALSE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R-sq. ',1,TRUE)
> a<-table.element(a, round(sumlmxdf$'r.squared', digits=3) ,nc, FALSE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-sq. ',1,TRUE)
> a<-table.element(a, round(sumlmxdf$'adj.r.squared', digits=3) ,nc, FALSE)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/1x3jo1304593906.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, ' ',1,TRUE)
> a<-table.element(a, 'Df',1,TRUE)
> a<-table.element(a, 'Sum Sq',1,TRUE)
> a<-table.element(a, 'Mean Sq',1,TRUE)
> a<-table.element(a, 'F value',1,TRUE)
> a<-table.element(a, 'Pr(>F)',1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, V2,1,TRUE)
> a<-table.element(a, anova.xdf$Df[1])
> a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3))
> a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3))
> a<-table.element(a, round(anova.xdf$'F value'[1], digits=3))
> a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residuals',1,TRUE)
> a<-table.element(a, anova.xdf$Df[2])
> a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3))
> a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3))
> a<-table.element(a, ' ')
> a<-table.element(a, ' ')
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/202l51304593906.tab") 
> postscript(file="/var/www/html/freestat/rcomp/tmp/3rlpp1304593906.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution')
> if(intercept == TRUE) abline(coef(lmxdf), col='red')
> if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red')
> dev.off()
null device 
          1 
> library(car)
Loading required package: MASS
Loading required package: nnet
Loading required package: survival
Loading required package: splines
> postscript(file="/var/www/html/freestat/rcomp/tmp/4qzji1304593906.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qq.plot(resid(lmxdf), main='QQplot of Residuals of Fit')
Warning message:
'qq.plot' is deprecated.
Use 'qqPlot' instead.
See help("Deprecated") and help("car-deprecated"). 
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/freestat/rcomp/tmp/5jf7n1304593906.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit')
> dev.off()
null device 
          1 
> 
> try(system("convert tmp/3rlpp1304593906.ps tmp/3rlpp1304593906.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qzji1304593906.ps tmp/4qzji1304593906.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jf7n1304593906.ps tmp/5jf7n1304593906.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.231   0.107   1.350