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(2.4,2.4,2.5,2.6,2.4,2.6,2.4,2.3,2.4,2.4,2.4,2.4,2.4,2.4,2.4,2.4,2.5,2.1,2.1,2,2,2,1.9,1.9,2,1.8,1.6,1.3,1.4,1.4,1.5,1.7,1.6,1.5,1.6,1.5,1.1,1.1,1.1,1.4,1.3,1.4,1.3,1.1,1,0.9,0.8,0.8,0.8,0.8,1,1.1,1,0.9,1.1,1.2,1.2,1.4,1.5,1.7,1.9,1.9,1.9,1.7,1.7,2.1,2,2,2.5,2.4,2.5,2.5,2,1.9,2.2,2.7,3.1,2.8,2.6,2.3,2.2,2.2,2,2,2.6,2.5,2.5,2.3,2,1.9,2,2.1,2.1,2.3,2.3,2.3,2.1,2.4,2.5,2.1,1.8,1.9,1.9,2.1,2.2,2,2.2,2,1.9,1.6,1.7,2,2.5,2.4,2.3,2.3,2.1,2.4,2.2,2.4,1.9,2.1,2.1,2.1,2,2.1,2.2,2.2,2.6,2.5,2.3,2.2,2.4,2.3,2.2,2.5,2.5,2.5,2.4,2.3,1.7,1.6,1.9,1.9,1.8,1.8,1.9,1.9,1.9,1.9,1.8,1.7,2.1,2.6,3.1,3.1,3.2,3.3,3.6,3.3,3.7,4,4,3.8,3.6,3.2,2.1,1.6,1.1,1.2,0.6,0.6,0,-0.1,-0.6,-0.2,-0.3,-0.1,0.5,0.9)
> x <- c(10.47,10.44,10.41,10.37,10.38,10.38,10.37,10.41,10.44,10.43,10.47,10.49,10.53,10.63,10.66,10.66,10.64,10.65,10.61,10.6,10.61,10.63,10.63,10.61,10.7,10.69,10.62,10.62,10.63,10.62,10.53,10.51,10.5,10.52,10.47,10.43,10.35,10.31,10.25,10.26,10.2,10.13,10.06,10.01,9.95,9.92,9.87,9.83,9.7,9.63,9.56,9.53,9.47,9.4,9.32,9.26,9.19,9.1,9.03,8.95,8.85,8.78,8.71,8.61,8.54,8.49,8.42,8.36,8.3,8.19,8.15,8.1,8.04,8.05,8.04,8,8.02,8,8,8.01,8.04,8.1,8.14,8.17,8.17,8.22,8.21,8.29,8.37,8.43,8.47,8.51,8.55,8.59,8.66,8.71,8.78,8.81,8.84,8.81,8.82,8.84,8.83,8.83,8.88,8.88,8.89,8.93,8.95,8.92,8.97,8.99,9.01,8.99,9.03,9.04,9.07,9.04,9.07,9.09,9.04,9.08,9.13,9.09,9.05,9.06,8.99,8.98,8.99,8.94,8.87,8.83,8.8,8.79,8.71,8.6,8.5,8.38,8.26,8.23,8.17,8.1,8.02,7.9,7.82,7.72,7.63,7.53,7.56,7.49,7.53,7.47,7.39,7.37,7.34,7.39,7.32,7.24,7.18,7.31,7.39,7.48,7.51,7.61,7.69,7.86,8.05,8.24,8.55,8.81,9.13,9.24,9.36,9.48,9.61,9.7,9.82,9.86,9.87,9.87)
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = ''
> par2 = ''
> 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 
-2.38654 -0.40235  0.05654  0.42069  1.55144 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  4.81609    0.46074  10.453  < 2e-16 ***
x           -0.31525    0.05059  -6.231 3.25e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.6862 on 178 degrees of freedom
Multiple R-squared: 0.1791,	Adjusted R-squared: 0.1745 
F-statistic: 38.83 on 1 and 178 DF,  p-value: 3.251e-09 

> postscript(file="/var/wessaorg/rcomp/tmp/1pq151321397629.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/2z3ak1321397629.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 
-3.478e-16 -7.729e-17  1.690e-18  8.338e-17  2.353e-16 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  4.816e+00  8.249e-17  5.838e+16   <2e-16 ***
x           -3.153e-01  9.058e-18 -3.480e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.229e-16 on 178 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.211e+33 on 1 and 178 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3qph01321397629.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-2.38654 -0.40235  0.05654  0.42069  1.55144 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  4.385e-17  4.607e-01       0        1
x           -2.970e-18  5.059e-02       0        1

Residual standard error: 0.6862 on 178 degrees of freedom
Multiple R-squared: 9.115e-34,	Adjusted R-squared: -0.005618 
F-statistic: 1.622e-31 on 1 and 178 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/413v51321397629.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-0.5199 -0.2763  0.0334  0.2596  0.5898 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.963e+00  2.389e-02   82.16   <2e-16 ***
m$residuals -6.878e-18  3.501e-02    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.3205 on 178 degrees of freedom
Multiple R-squared: 4.314e-32,	Adjusted R-squared: -0.005618 
F-statistic: 7.68e-30 on 1 and 178 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/55fdl1321397629.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 
-0.97810 -0.12483 -0.00192  0.12512  0.59441 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.009161   0.017544  -0.522    0.602    
Residuals    0.938678   0.025738  36.471   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.2347 on 177 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8826,	Adjusted R-squared: 0.8819 
F-statistic:  1330 on 1 and 177 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/68xnm1321397629.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7e99i1321397629.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/83sat1321397629.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9jcyi1321397629.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/10f8361321397629.tab") 
> 
> try(system("convert tmp/1pq151321397629.ps tmp/1pq151321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/2z3ak1321397629.ps tmp/2z3ak1321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qph01321397629.ps tmp/3qph01321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/413v51321397629.ps tmp/413v51321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/55fdl1321397629.ps tmp/55fdl1321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/68xnm1321397629.ps tmp/68xnm1321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/7e99i1321397629.ps tmp/7e99i1321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/83sat1321397629.ps tmp/83sat1321397629.png",intern=TRUE))
character(0)
> try(system("convert tmp/9jcyi1321397629.ps tmp/9jcyi1321397629.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.686   0.509   3.337