R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> y <- c(2,2,2,1,2,2,2,2,2,2,1,2,1,2,2,1,1,2,1,2,1,2,2,2,1,2,1,2,2,1,2,1,2,2,1,1,1,1,2,1,1,2,1,1,2,2,2,2,2,1,2,1,1,2,1,2,2,2,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,1,2,2,2,1,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,2,2,2,1,2,1,2,2,2,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,1,2,1,2,1,2,2,1,1,1,2,2,1,2,2,2,2,2,2,2,2,2)
> x <- c(41,39,30,31,34,35,39,34,36,37,38,36,38,39,33,32,36,38,39,32,32,31,39,37,39,41,36,33,33,34,31,27,37,34,34,32,29,36,29,35,37,34,38,35,38,37,38,33,36,38,32,32,32,34,32,37,39,29,37,35,30,38,34,31,34,35,36,30,39,35,38,31,34,38,34,39,37,34,28,37,33,37,35,37,32,33,38,33,29,33,31,36,35,32,29,39,37,35,37,32,38,37,36,32,33,40,38,41,36,43,30,31,32,32,37,37,33,34,33,38,33,31,38,37,33,31,39,44,33,35,32,28,40,27,37,32,28,34,30,35,31,32,30,30,31,40,32,36,32,35,38,42,34,35,35,33,36,32,33,34,32,34)
> 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 
-0.6827 -0.5991  0.3452  0.3893  0.4288 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)   
(Intercept) 1.301942   0.395195   3.294  0.00121 **
x           0.009286   0.011361   0.817  0.41492   
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.4865 on 160 degrees of freedom
Multiple R-squared: 0.004158,	Adjusted R-squared: -0.002066 
F-statistic: 0.6681 on 1 and 160 DF,  p-value: 0.4149 

> postscript(file="/var/wessaorg/rcomp/tmp/1k0vj1321294061.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/wessaorg/rcomp/tmp/2l1sr1321294061.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 
-1.104e-16 -4.678e-17 -1.153e-17  1.334e-17  2.513e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.302e+00  1.649e-16 7.896e+15   <2e-16 ***
x           9.286e-03  4.740e-18 1.959e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.03e-16 on 160 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 3.838e+30 on 1 and 160 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/34tcq1321294061.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-0.6827 -0.5991  0.3452  0.3893  0.4288 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  4.129e-17  3.952e-01       0        1
x           -8.285e-19  1.136e-02       0        1

Residual standard error: 0.4865 on 160 degrees of freedom
Multiple R-squared:     0,	Adjusted R-squared: -0.00625 
F-statistic:     0 on 1 and 160 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4va511321294061.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-0.070792 -0.024361 -0.005789  0.022069  0.087071 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.623e+00  2.470e-03   657.2   <2e-16 ***
m$residuals 2.701e-17  5.109e-03     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.03144 on 160 degrees of freedom
Multiple R-squared: 5.269e-29,	Adjusted R-squared: -0.00625 
F-statistic: 8.43e-27 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/wessaorg/rcomp/tmp/590oj1321294061.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 
-0.7050 -0.5898  0.3213  0.4002  0.4644 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.002169   0.038279  -0.057    0.955
Residuals   -0.083497   0.079076  -1.056    0.293

Residual standard error: 0.4857 on 159 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.006963,	Adjusted R-squared: 0.0007178 
F-statistic: 1.115 on 1 and 159 DF,  p-value: 0.2926 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6o5fi1321294061.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7ecrr1321294061.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/81ajl1321294061.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9be5x1321294061.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/10fyok1321294061.tab") 
> 
> try(system("convert tmp/1k0vj1321294061.ps tmp/1k0vj1321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/2l1sr1321294061.ps tmp/2l1sr1321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/34tcq1321294061.ps tmp/34tcq1321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/4va511321294061.ps tmp/4va511321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/590oj1321294061.ps tmp/590oj1321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/6o5fi1321294061.ps tmp/6o5fi1321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ecrr1321294061.ps tmp/7ecrr1321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/81ajl1321294061.ps tmp/81ajl1321294061.png",intern=TRUE))
character(0)
> try(system("convert tmp/9be5x1321294061.ps tmp/9be5x1321294061.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.631   0.494   3.171