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(57.8,52.5,58.2,61.1,65.7,62.3,63.3,62.6,61.9,63.9,64.2,64.8,55.1,56.2,63.7,62.6,58.4,55.5,66.6,54.7,58.9,51.3,51,48.9,52.6,51.2,59.6,63,61.4,59.3,58.6,63.6,66.9,68.9,64.2,63.1,63.3,60.1,59.2,55.3,56.6,58.9,60.3,60.1,60.8,60.7,61.8,69.5,62.2,60.7,63.4,69.7,64.2,63.8,64.1,63.2,62.2,65.4,61.2,60.8,59.1,55.9)
> x <- c(18.4,17.6,19,20.5,24.3,21.2,22.1,21.5,20.8,22.5,23.7,23.8,14.1,16.3,22.2,21.1,19.2,17.3,20.8,22.6,20.2,18.6,17,13.3,19.7,18.6,21.7,24.3,18.9,16.8,18.1,21.7,26.7,23.4,25.3,22.9,24.6,20.5,19.1,17.3,20.1,21.1,21.1,20,21.3,21.1,21.8,22.2,19.4,19.7,23.1,27.4,23.4,24.2,20.9,24.2,20.9,24.2,21.2,18.3,16.6,17.9)
> 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 
-8.1784 -1.0848  0.1367  1.3131  7.1238 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  34.5068     2.7420  12.585  < 2e-16 ***
x             1.2554     0.1308   9.596 9.94e-14 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.892 on 60 degrees of freedom
Multiple R-squared: 0.6055,	Adjusted R-squared: 0.5989 
F-statistic: 92.09 on 1 and 60 DF,  p-value: 9.937e-14 

> postscript(file="/var/wessaorg/rcomp/tmp/1cuzn1321288112.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/21zzd1321288112.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 
-1.030e-14 -1.591e-15  2.086e-16  2.078e-15  7.783e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 3.451e+01  2.927e-15 1.179e+16   <2e-16 ***
x           1.255e+00  1.396e-16 8.990e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.087e-15 on 60 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 8.082e+31 on 1 and 60 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/38q3k1321288112.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-8.1784 -1.0848  0.1367  1.3131  7.1238 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -7.584e-16  2.742e+00       0        1
x            3.667e-17  1.308e-01       0        1

Residual standard error: 2.892 on 60 degrees of freedom
Multiple R-squared: 4.385e-33,	Adjusted R-squared: -0.01667 
F-statistic: 2.631e-31 on 1 and 60 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4etcf1321288112.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-9.3789 -2.3174  0.2875  2.2647  8.3220 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  6.058e+01  4.550e-01   133.2   <2e-16 ***
m$residuals -1.194e-16  1.599e-01     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.582 on 60 degrees of freedom
Multiple R-squared: 2.229e-30,	Adjusted R-squared: -0.01667 
F-statistic: 1.338e-28 on 1 and 60 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/5bq6n1321288112.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 
-9.6974 -1.0998  0.3989  1.0114  7.1504 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)  
(Intercept) -0.007695   0.361009  -0.021   0.9831  
Residuals    0.255253   0.126030   2.025   0.0474 *
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.82 on 59 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.06501,	Adjusted R-squared: 0.04916 
F-statistic: 4.102 on 1 and 59 DF,  p-value: 0.04736 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6j0gt1321288112.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7cls01321288112.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8cn2p1321288112.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9h1dj1321288112.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/101cw91321288112.tab") 
> 
> try(system("convert tmp/1cuzn1321288112.ps tmp/1cuzn1321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/21zzd1321288112.ps tmp/21zzd1321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/38q3k1321288112.ps tmp/38q3k1321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/4etcf1321288112.ps tmp/4etcf1321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/5bq6n1321288112.ps tmp/5bq6n1321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/6j0gt1321288112.ps tmp/6j0gt1321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/7cls01321288112.ps tmp/7cls01321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/8cn2p1321288112.ps tmp/8cn2p1321288112.png",intern=TRUE))
character(0)
> try(system("convert tmp/9h1dj1321288112.ps tmp/9h1dj1321288112.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.506   0.464   2.979