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(8054,9,7968,7,5935,7,7455,6,3347,6,6972,6,3983,5,4481,5,2946,5,3560,5,2747,5,3101,5,7491,4,2058,4,1837,4,2197,4,3572,4,4686,4,3113,4,1251,4,5418,3,1746,3,1310,3,1658,3,1718,3,1665,3,1862,3,3084,3,1143,3,1273,3,2983,3,2752,3,1710,3,1915,3,1120,3,3015,3,1044,3,420,3,1213,3,2998,3,1228,3,1135,3,1632,3,3239,3,509,3,3358,3,1789,2,2574,2,1023,2,2163,2,689,2,1652,2,3186,2,2408,2,286,2,1638,2,1080,2,2973,2,1784,2,1224,2,1582,2,2197,2,1103,2,1414,2,1250,2,437,2,551,2,1457,2,1602,2,1366,2,1326,2,149,2,1709,2,515,2,449,2,707,2,666,2,651,2,168,2,625,1,443,1,502,1,2042,1,1401,1,594,1,2144,1,1535,1,1436,1,69,1,1279,1,383,1,50,1,970,1,941,1,519,1,1230,1,315,1,329,1,560,1,105,1,268,1,76,1,16,1,391,1,209,1,219,1,741,1,16,0,134,0,10,0,19,0,18,0,86,0,101,0,17,0,5,0,14,0,1,0,1,0),dim=c(2,119),dimnames=list(c('Revisions','Hours'),1:119))
>  y <- array(NA,dim=c(2,119),dimnames=list(c('Revisions','Hours'),1:119))
>  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] "Revisions"
> (V2<-dimnames(y)[[1]][cat2])
[1] "Hours"
> 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  
     -307.9        865.9  

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

Terms:
                        X Residuals
Sum of Squares  242558001 116423956
Deg. of Freedom         1       117

Residual standard error: 997.5352 
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 242558001 242558001  243.76 < 2.2e-16 ***
Residuals 117 116423956    995077                      
---
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/1dsmo1355943709.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/22rtj1355943709.tab") 
> postscript(file="/var/wessaorg/rcomp/tmp/3r4rc1355943709.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/4qru81355943709.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/589011355943709.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/66k411355943709.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/3r4rc1355943709.ps tmp/3r4rc1355943709.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qru81355943709.ps tmp/4qru81355943709.png",intern=TRUE))
character(0)
> try(system("convert tmp/589011355943709.ps tmp/589011355943709.png",intern=TRUE))
character(0)
> try(system("convert tmp/66k411355943709.ps tmp/66k411355943709.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.662   0.486   3.142