R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> y <- c(12,8,8,8,9,7,4,11,7,7,12,10,10,8,8,4,9,8,7,11,9,11,13,8,8,9,6,9,9,6,6,16,5,7,9,6,6,5,12,7,10,9,8,5,8,8,10,6,8,7,4,8,8,4,20,8,8,6,4,8,9,6,7,9,5,5,8,8,6,8,7,7,9,11,6,8,6,9,8,6,10,8,8,10,5,7,5,8,14,7,8,6,5,6,10,12,9,12,7,8,10,6,10,10,10,5,7,10,11,6,7,12,11,11,11,5,8,6,9,4,4,7,11,6,7,8,4,8,9,8,11,8,5,4,8,10,6,9,9,13,9,10,20,5,11,6,9,7,9,10,9,8,7,6,13,6,8,10,16)
> x <- c(14,11,6,12,8,10,10,11,16,11,13,12,8,12,11,4,9,8,8,14,15,16,9,14,11,8,9,9,9,9,10,16,11,8,9,16,11,16,12,12,14,9,10,9,10,12,14,14,10,14,16,9,10,6,8,13,10,8,7,15,9,10,12,13,10,11,8,9,13,11,8,9,9,15,9,10,14,12,12,11,14,6,12,8,14,11,10,14,12,10,14,5,11,10,9,10,16,13,9,10,10,7,9,8,14,14,8,9,14,14,8,8,8,7,6,8,6,11,14,11,11,11,14,8,20,11,8,11,10,14,11,9,9,8,10,13,13,12,8,13,14,12,14,15,13,16,9,9,9,8,7,16,11,9,11,9,14,13,16)
> par1 = '0'
> 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 
-4.9882 -1.9440 -0.2424  1.3101 12.2051 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  6.60149    0.85711   7.702 1.41e-12 ***
x            0.14917    0.07622   1.957   0.0521 .  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.683 on 157 degrees of freedom
Multiple R-squared: 0.02381,	Adjusted R-squared: 0.0176 
F-statistic:  3.83 on 1 and 157 DF,  p-value: 0.05211 

> postscript(file="/var/www/rcomp/tmp/1givj1321399907.ps",horizontal=F,onefile=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/2qxkr1321399907.ps",horizontal=F,onefile=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 
-1.047e-14 -3.452e-16  7.120e-17  4.963e-16  1.256e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 6.601e+00  3.229e-16 2.044e+16   <2e-16 ***
x           1.492e-01  2.872e-17 5.195e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.011e-15 on 157 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.699e+31 on 1 and 157 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3k2ee1321399907.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-4.9882 -1.9440 -0.2424  1.3101 12.2051 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.738e-17  8.571e-01       0        1
x            7.017e-18  7.622e-02       0        1

Residual standard error: 2.683 on 157 degrees of freedom
Multiple R-squared: 6.637e-35,	Adjusted R-squared: -0.006369 
F-statistic: 1.042e-32 on 1 and 157 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/4w48j1321399907.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-1.02824 -0.28239  0.01595  0.31429  1.35848 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  8.226e+00  3.324e-02   247.5   <2e-16 ***
m$residuals -7.002e-17  1.247e-02     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.4191 on 157 degrees of freedom
Multiple R-squared: 8.01e-30,	Adjusted R-squared: -0.006369 
F-statistic: 1.258e-27 on 1 and 157 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/53ufd1321399907.ps",horizontal=F,onefile=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 
-5.0790 -1.7762 -0.2619  1.2627 11.9918 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.02396    0.21265  -0.113    0.910
Residuals   -0.06788    0.08129  -0.835    0.405

Residual standard error: 2.673 on 156 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.004449,	Adjusted R-squared: -0.001933 
F-statistic: 0.6971 on 1 and 156 DF,  p-value: 0.405 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/6e25u1321399907.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/79hng1321399907.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/88xcp1321399907.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/9g8961321399907.ps",horizontal=F,onefile=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/106tyq1321399907.tab") 
> 
> try(system("convert tmp/1givj1321399907.ps tmp/1givj1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qxkr1321399907.ps tmp/2qxkr1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/3k2ee1321399907.ps tmp/3k2ee1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/4w48j1321399907.ps tmp/4w48j1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/53ufd1321399907.ps tmp/53ufd1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/6e25u1321399907.ps tmp/6e25u1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/79hng1321399907.ps tmp/79hng1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/88xcp1321399907.ps tmp/88xcp1321399907.png",intern=TRUE))
character(0)
> try(system("convert tmp/9g8961321399907.ps tmp/9g8961321399907.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.340   0.556   4.295