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(71.91,6.06,8.10,79.38,65.34,34.62,26.26,60.92,39.56,65.61,56.49,56.19,80.30,61.20,58.20,75.91,73.66,73.87,87.21,64.29,71.82,89.31,1.41,35.17,34.68,41.08,30.57,68.84,7.17,71.05,23.32,61.39,8.41,65.88,64.06,26.80,12.78,23.84,42.69,54.94,89.99,5.68,72.64,45.92,24.96,18.17,29.12,40.08,1.08,57.52)
> x <- c(5.11,3.53,4.52,3.72,5.99,3.15,3.17,3.50,3.39,4.15,4.50,3.31,3.09,5.31,4.24,5.06,4.72,4.58,5.30,5.11,4.05,4.62,4.66,4.66,2.76,5.10,4.97,2.87,5.14,4.98,4.55,5.45,4.36,4.78,4.74,5.44,5.78,2.92,4.22,3.93,3.01,3.22,5.12,3.04,5.82,3.11,3.87,3.75,4.82,2.83)
> 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 
-46.943 -21.147   8.493  21.730  44.362 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)  
(Intercept)   41.645     17.980   2.316   0.0249 *
x              1.323      4.110   0.322   0.7489  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 26.23 on 48 degrees of freedom
Multiple R-squared: 0.002154,	Adjusted R-squared: -0.01863 
F-statistic: 0.1036 on 1 and 48 DF,  p-value: 0.7489 

> postscript(file="/var/wessaorg/rcomp/tmp/1zznl1321370327.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/2510m1321370327.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 
-6.932e-15 -2.391e-15  1.760e-17  1.473e-15  1.833e-14 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 4.165e+01  2.839e-15 1.467e+16   <2e-16 ***
x           1.323e+00  6.491e-16 2.039e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4.143e-15 on 48 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 4.156e+30 on 1 and 48 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3cu281321370327.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-46.943 -21.147   8.493  21.730  44.362 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.236e-15  1.798e+01       0        1
x            3.957e-16  4.110e+00       0        1

Residual standard error: 26.23 on 48 degrees of freedom
Multiple R-squared: 5.383e-33,	Adjusted R-squared: -0.02083 
F-statistic: 2.584e-31 on 1 and 48 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/43vn51321370327.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-2.0117 -1.1418  0.3038  1.0051  2.2621 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 4.731e+01  1.724e-01   274.4   <2e-16 ***
m$residuals 3.851e-18  6.707e-03     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.219 on 48 degrees of freedom
Multiple R-squared: 1.416e-30,	Adjusted R-squared: -0.02083 
F-statistic: 6.795e-29 on 1 and 48 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/5i1y31321370327.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 
-46.436 -21.034   8.593  18.980  44.806 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.478598   3.755065  -0.127    0.899
Residuals    0.004287   0.144944   0.030    0.977

Residual standard error: 26.28 on 47 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 1.861e-05,	Adjusted R-squared: -0.02126 
F-statistic: 0.0008748 on 1 and 47 DF,  p-value: 0.9765 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6sv8d1321370327.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7lypa1321370327.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/88ww81321370327.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9wku11321370327.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/10muny1321370327.tab") 
> 
> try(system("convert tmp/1zznl1321370327.ps tmp/1zznl1321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/2510m1321370327.ps tmp/2510m1321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/3cu281321370327.ps tmp/3cu281321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/43vn51321370327.ps tmp/43vn51321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/5i1y31321370327.ps tmp/5i1y31321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/6sv8d1321370327.ps tmp/6sv8d1321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/7lypa1321370327.ps tmp/7lypa1321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/88ww81321370327.ps tmp/88ww81321370327.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wku11321370327.ps tmp/9wku11321370327.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.432   0.416   2.885