R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(2,2,2,1,3,2,3,1,1,2,3,1,1,2,1,2,3,3,1,4,1,2,1,2,3,1,2,3,2,2,1,3,1,2,3,1,4,2,1,1,1,3,1,2,1,2,1,1,3,2,1,1,2,2,2,1,1,1,3,2,3,1,1,1,2,2,2,3,1,1,2,2,1,2,2,2,2,2,3,1,1,1,1,1,1,4,2,2,1,4,4,3,3,2,3,3,3,2,1,1,1,3,2,4,4,3,2,1,1,4,1,2,2,4,2,1,2,1,1,3,1,3,3,1,2,2,1,3,2,3,2,4,1,3,1,3,2,2,3,3,3,2,4,2,1,1,2,3,2,4,3,4,2,3,2,2,3,4,2,1,3,1)
> x <- c(1,1,1,1,2,1,4,1,1,2,1,1,2,1,1,1,1,1,1,2,1,2,1,2,1,1,1,2,1,1,1,2,1,1,1,1,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,1,1,1,2,1,1,2,1,1,1,1,1,2,1,1,2,1,1,1,1,1,3,2,2,1,1,1,1,1,1,1,1,1,1,1,3,1,1,1,1,1,1,1,1,1,1,1,2,1,1,1,2,1,2,2,3,2,2,1,1,1,1,1,1,1,1,2,1,1,1,1,1,1,1,1,1,2,2,1,1,1,1,4,1,2,1,1,1,1,1,1,1,1,1,1,2,1,2,1,1,3,1,1,1,1,1,2,1)
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = ''
> par2 = ''
> par1 = '0'
> ylab = ''
> xlab = ''
> main = ''
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> library(lattice)
> z <- as.data.frame(cbind(x,y))
> m <- lm(y~x)
> summary(m)

Call:
lm(formula = y ~ x)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.32922 -0.95351  0.04649  1.04649  2.04649 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   1.5778     0.1813   8.705 3.71e-15 ***
x             0.3757     0.1302   2.886  0.00444 ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.9393 on 160 degrees of freedom
Multiple R-squared: 0.04948,	Adjusted R-squared: 0.04354 
F-statistic: 8.328 on 1 and 160 DF,  p-value: 0.004442 

> postscript(file="/var/www/rcomp/tmp/1k1pb1289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(z,main='Scatterplot, lowess, and regression line')
> lines(lowess(z),col='red')
> abline(m)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/2da6d1289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m2 <- lm(m$fitted.values ~ x)
> summary(m2)

Call:
lm(formula = m$fitted.values ~ x)

Residuals:
       Min         1Q     Median         3Q        Max 
-3.524e-16 -1.303e-16  9.171e-17  9.171e-17  1.964e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.578e+00  3.886e-17 4.061e+16   <2e-16 ***
x           3.757e-01  2.791e-17 1.346e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.013e-16 on 160 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.812e+32 on 1 and 160 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3o1oy1289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

Call:
lm(formula = m$residuals ~ x)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.32922 -0.95351  0.04649  1.04649  2.04649 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -3.252e-17  1.813e-01 -1.79e-16        1
x            6.813e-18  1.302e-01  5.23e-17        1

Residual standard error: 0.9393 on 160 degrees of freedom
Multiple R-squared: 9.873e-34,	Adjusted R-squared: -0.00625 
F-statistic: 1.58e-31 on 1 and 160 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/4htn11289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

Call:
lm(formula = m$fitted.values ~ m$residuals)

Residuals:
    Min      1Q  Median      3Q     Max 
-0.1020 -0.1020 -0.1020 -0.1020  1.0251 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  2.056e+00  1.684e-02     122.1   <2e-16 ***
m$residuals -4.996e-17  1.804e-02 -2.77e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.2143 on 160 degrees of freedom
Multiple R-squared: 2.684e-30,	Adjusted R-squared: -0.00625 
F-statistic: 4.295e-28 on 1 and 160 DF,  p-value: 1 

> z4 <- as.data.frame(cbind(m$residuals,m$fitted.values))
> names(z4) <- list('Residuals','Fitted')
> plot(z4,main='Scatterplot, lowess, and regression line')
> lines(lowess(z4),col='red')
> abline(m4)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/5htn11289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> myr <- as.ts(m$residuals)
> z5 <- as.data.frame(cbind(lag(myr,1),myr))
> names(z5) <- list('Lagged Residuals','Residuals')
> plot(z5,main='Lag plot')
> m5 <- lm(z5)
> summary(m5)

Call:
lm(formula = z5)

Residuals:
       Min         1Q     Median         3Q        Max 
-1.3875299 -0.9096117 -0.0005195  0.9711041  2.0903883 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.000558   0.074181  -0.008    0.994
Residuals    0.045454   0.079481   0.572    0.568

Residual standard error: 0.9412 on 159 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.002053,	Adjusted R-squared: -0.004224 
F-statistic: 0.3271 on 1 and 159 DF,  p-value: 0.5682 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/62bm71289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/72bm71289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/82bm71289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/92bm71289973747.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Simple Linear Regression',5,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Statistics',1,TRUE)
> a<-table.element(a,'Estimate',1,TRUE)
> a<-table.element(a,'S.D.',1,TRUE)
> a<-table.element(a,'T-STAT (H0: coeff=0)',1,TRUE)
> a<-table.element(a,'P-value (two-sided)',1,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'constant term',header=TRUE)
> a<-table.element(a,m$coefficients[[1]])
> sd <- sqrt(vcov(m)[1,1])
> a<-table.element(a,sd)
> tstat <- m$coefficients[[1]]/sd
> a<-table.element(a,tstat)
> pval <- 2*(1-pt(abs(tstat),length(x)-2))
> a<-table.element(a,pval)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'slope',header=TRUE)
> a<-table.element(a,m$coefficients[[2]])
> sd <- sqrt(vcov(m)[2,2])
> a<-table.element(a,sd)
> tstat <- m$coefficients[[2]]/sd
> a<-table.element(a,tstat)
> pval <- 2*(1-pt(abs(tstat),length(x)-2))
> a<-table.element(a,pval)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/10gl1g1289973747.tab") 
> 
> try(system("convert tmp/1k1pb1289973747.ps tmp/1k1pb1289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/2da6d1289973747.ps tmp/2da6d1289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o1oy1289973747.ps tmp/3o1oy1289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/4htn11289973747.ps tmp/4htn11289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/5htn11289973747.ps tmp/5htn11289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/62bm71289973747.ps tmp/62bm71289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/72bm71289973747.ps tmp/72bm71289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/82bm71289973747.ps tmp/82bm71289973747.png",intern=TRUE))
character(0)
> try(system("convert tmp/92bm71289973747.ps tmp/92bm71289973747.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.020   0.790   3.797