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(0.439620618
+ ,65.2261159
+ ,0.415578668
+ ,66.18192324
+ ,0.374927888
+ ,68.51084108
+ ,0.347499866
+ ,70.33722683
+ ,0.327363973
+ ,71.143908
+ ,0.30912795
+ ,71.73414119
+ ,0.294782014
+ ,71.99927612
+ ,0.271568014
+ ,73.59456359
+ ,0.24362019
+ ,76.89891122
+ ,0.219233356
+ ,78.58059708
+ ,0.198928656
+ ,81.23539893
+ ,0.153201781
+ ,90.76678766
+ ,0.136500202
+ ,92.88460144
+ ,0.1247118
+ ,93.66937745
+ ,0.125838095
+ ,88.60410226
+ ,0.136887675
+ ,79.25341207
+ ,0.124547993
+ ,77.2465582
+ ,0.107159561
+ ,81.65647728
+ ,0.104998434
+ ,79.13140312
+ ,0.107308572
+ ,75.54106548
+ ,0.104528533
+ ,73.37597484
+ ,0.08088668
+ ,76.58704251
+ ,0.059476192
+ ,86.94640339
+ ,0.053914856
+ ,92.58089844
+ ,0.051123828
+ ,92.06547505
+ ,0.046363275
+ ,94.67242843
+ ,0.044694892
+ ,94.25869487
+ ,0.040634361
+ ,99.41227085
+ ,0.038625779
+ ,98.61304918
+ ,0.040071656
+ ,96.84902718
+ ,0.039128976
+ ,95.23722912
+ ,0.03841219
+ ,96.77880196
+ ,0.037037037
+ ,96.9227634
+ ,0.034563019
+ ,99.45702834
+ ,0.033502125
+ ,99.64352421
+ ,0.034427132
+ ,98.73290651
+ ,0.032522094
+ ,99.24435175
+ ,0.028919522
+ ,106.3037831
+ ,0.028209468
+ ,106.1372524
+ ,0.030091905
+ ,104.0509283
+ ,0.031718983
+ ,101.0545734
+ ,0.032220944
+ ,100
+ ,0.030558106
+ ,100.8805611
+ ,0.028205662
+ ,101.6755514
+ ,0.023910542
+ ,106.8457317)
+ ,dim=c(2
+ ,45)
+ ,dimnames=list(c('ConsOV'
+ ,'Pov')
+ ,1:45))
>  y <- array(NA,dim=c(2,45),dimnames=list(c('ConsOV','Pov'),1:45))
>  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'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: aston2
> #To cite this work: Ian E. Holliday, 2012, Simple Linear Regression (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/Ian.Holliday/rwasp_Simple%20Regression%20Y%20~%20X.wasp/
> #Source of accompanying publication: 
> #
> 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] "ConsOV"
> (V2<-dimnames(y)[[1]][cat2])
[1] "Pov"
> 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  
   0.852996    -0.008251  

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

Terms:
                        X Residuals
Sum of Squares  0.4719695 0.1600274
Deg. of Freedom         1        43

Residual standard error: 0.06100465 
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 0.47197 0.47197  126.82 2.078e-14 ***
Residuals 43 0.16003 0.00372                      
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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)
+ }
+ a<-table.row.end(a)
+ }
> 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/wessaorg/rcomp/tmp/1ajr31356031667.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/wessaorg/rcomp/tmp/2zxnu1356031667.tab") 
> postscript(file="/var/wessaorg/rcomp/tmp/3omy31356031667.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
> postscript(file="/var/wessaorg/rcomp/tmp/4a0cs1356031667.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/wessaorg/rcomp/tmp/59b9u1356031667.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 
> postscript(file="/var/wessaorg/rcomp/tmp/6c79k1356031667.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot.lm(lmxdf, which=4)
> dev.off()
null device 
          1 
> 
> try(system("convert tmp/3omy31356031667.ps tmp/3omy31356031667.png",intern=TRUE))
character(0)
> try(system("convert tmp/4a0cs1356031667.ps tmp/4a0cs1356031667.png",intern=TRUE))
character(0)
> try(system("convert tmp/59b9u1356031667.ps tmp/59b9u1356031667.png",intern=TRUE))
character(0)
> try(system("convert tmp/6c79k1356031667.ps tmp/6c79k1356031667.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.347   0.506   2.895