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(12,11,14,12,21,12,22,11,10,13,10,8,15,14,10,14,14,11,10,13,7,14,12,14,11,9,11,15,14,13,9,15,10,11,13,8,20,12,10,10,9,14,8,14,11,13,9,11,15,11,10,14,18,14,11,12,13,9,10,15,20,12,12,14,13,11,17,12,13,14,13,15,13,10,11,19,13,17,13,9,11,10,9,12,12,13,13,12,15,22,13,15,13,15,10,11,16,11,11,10,10,16,12,11,16,19,11,16,15,24,14,15,11,15,12,10)
> x <- c(14,18,11,12,16,18,14,14,15,15,17,19,10,16,18,14,14,17,14,16,18,11,14,12,17,9,16,14,15,11,16,13,17,15,14,16,9,15,17,13,15,16,16,12,12,11,15,15,17,13,16,14,11,12,12,15,16,15,12,12,8,13,11,14,15,10,11,12,15,15,14,16,15,15,13,12,17,13,15,13,15,16,15,16,15,14,15,14,13,7,17,13,15,14,13,16,12,14,17,15,17,12,16,11,15,9,16,15,10,10,15,11,13,14,18,16)
> 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 
-7.1549 -1.8498 -0.1857  1.5412  9.4400 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  22.0627     1.5136  14.576  < 2e-16 ***
x            -0.6564     0.1061  -6.187 9.87e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.708 on 114 degrees of freedom
Multiple R-squared: 0.2514,	Adjusted R-squared: 0.2448 
F-statistic: 38.28 on 1 and 114 DF,  p-value: 9.867e-09 

> postscript(file="/var/wessaorg/rcomp/tmp/15hq41321371323.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/290hb1321371323.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 
-2.456e-15 -7.910e-17  4.120e-17  1.222e-16  7.247e-15 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  2.206e+01  4.830e-16  4.567e+16   <2e-16 ***
x           -6.564e-01  3.386e-17 -1.939e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 8.641e-16 on 114 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 3.759e+32 on 1 and 114 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/32sjo1321371323.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-7.1549 -1.8498 -0.1857  1.5412  9.4400 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  1.014e-16  1.514e+00       0        1
x           -7.064e-18  1.061e-01       0        1

Residual standard error: 2.708 on 114 degrees of freedom
Multiple R-squared:     0,	Adjusted R-squared: -0.008772 
F-statistic:     0 on 1 and 114 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4vfz51321371323.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-3.2368 -1.2676 -0.2829  1.3581  4.6402 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.283e+01  1.457e-01   88.05   <2e-16 ***
m$residuals -1.892e-17  5.428e-02    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.569 on 114 degrees of freedom
Multiple R-squared: 4.047e-31,	Adjusted R-squared: -0.008772 
F-statistic: 4.613e-29 on 1 and 114 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/58l4n1321371323.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 
-7.163 -1.872 -0.190  1.592  9.440 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.007541   0.253501   0.030    0.976
Residuals   0.003646   0.094167   0.039    0.969

Residual standard error: 2.718 on 113 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 1.327e-05,	Adjusted R-squared: -0.008836 
F-statistic: 0.001499 on 1 and 113 DF,  p-value: 0.9692 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6uqlp1321371323.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/73z8z1321371324.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8bqcg1321371324.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/982kh1321371324.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/1022s51321371324.tab") 
> 
> try(system("convert tmp/15hq41321371323.ps tmp/15hq41321371323.png",intern=TRUE))
character(0)
> try(system("convert tmp/290hb1321371323.ps tmp/290hb1321371323.png",intern=TRUE))
character(0)
> try(system("convert tmp/32sjo1321371323.ps tmp/32sjo1321371323.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vfz51321371323.ps tmp/4vfz51321371323.png",intern=TRUE))
character(0)
> try(system("convert tmp/58l4n1321371323.ps tmp/58l4n1321371323.png",intern=TRUE))
character(0)
> try(system("convert tmp/6uqlp1321371323.ps tmp/6uqlp1321371323.png",intern=TRUE))
character(0)
> try(system("convert tmp/73z8z1321371324.ps tmp/73z8z1321371324.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bqcg1321371324.ps tmp/8bqcg1321371324.png",intern=TRUE))
character(0)
> try(system("convert tmp/982kh1321371324.ps tmp/982kh1321371324.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.706   0.461   3.226