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(122.0,104.1,102.9,105.1,151.5,155.0,99.2,91.7,144.3,118.9,196.5,96.4,121.8,101.4,102.5,98.1,162.9,102.1,108.7,74.4,72.7,100.6,108.7,126.8,130.9,125.2,93.9,116.5,140.4,77.8,82.7,92.6,91.5,101.7,96.7,118.7,123.1,121.0,129.6,133.9,147.7,28.2,16.9,26.1,27.7,42.6,104.5,151.7,72.6,67.3,113.4,99.9,112.8,121.2,97.9,109.9,135.7,137.1,126.6,121.4)
> x <- c(122.0,126.0,127.4,123.5,137.4,153.2,107.4,84.6,98.0,100.2,104.4,93.9,122.0,126.0,127.4,123.5,137.4,153.2,93.8,99.3,95.0,95.6,107.7,106.7,117.4,118.9,118.0,95.2,95.8,107.8,106.7,117.3,119.0,118.3,105.9,116.3,131.9,93.7,99.3,95.0,95.6,107.7,106.8,117.3,118.9,117.9,116.4,123.0,138.7,98.8,108.5,103.9,310.1,420.9,90.8,96.1,86.8,84.0,127.3,135.8)
> 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 
-89.182 -10.188  -1.936  18.761  90.537 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 100.76902   11.58715   8.697 4.21e-12 ***
x             0.04975    0.08904   0.559    0.578    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 33.96 on 58 degrees of freedom
Multiple R-squared: 0.005354,	Adjusted R-squared: -0.0118 
F-statistic: 0.3122 on 1 and 58 DF,  p-value: 0.5785 

> postscript(file="/var/wessaorg/rcomp/tmp/13l941321390836.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/2oi5l1321390836.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 
-1.209e-14 -3.224e-15 -1.684e-15  3.047e-15  2.553e-14 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.008e+02  2.435e-15 4.139e+16   <2e-16 ***
x           4.975e-02  1.871e-17 2.659e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 7.137e-15 on 58 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 7.07e+30 on 1 and 58 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3gvlu1321390836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-89.182 -10.188  -1.936  18.761  90.537 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -4.590e-16  1.159e+01       0        1
x            1.959e-18  8.904e-02       0        1

Residual standard error: 33.96 on 58 degrees of freedom
Multiple R-squared: 9.266e-35,	Adjusted R-squared: -0.01724 
F-statistic: 5.374e-33 on 1 and 58 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/450yn1321390836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-1.8137 -1.0874 -0.4008  0.1514 14.9469 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.068e+02  3.217e-01   331.9   <2e-16 ***
m$residuals -9.180e-18  9.633e-03     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.492 on 58 degrees of freedom
Multiple R-squared: 1.262e-28,	Adjusted R-squared: -0.01724 
F-statistic: 7.319e-27 on 1 and 58 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/5k28k1321390836.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 
-96.631 -11.367   1.162  17.479  84.812 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  -0.1518     3.9824  -0.038 0.969720    
Residuals     0.4471     0.1184   3.775 0.000384 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 30.59 on 57 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared:   0.2,	Adjusted R-squared: 0.186 
F-statistic: 14.25 on 1 and 57 DF,  p-value: 0.0003838 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/61nuh1321390836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/77qb91321390836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8td9x1321390836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9yi1n1321390836.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/10179h1321390836.tab") 
> 
> try(system("convert tmp/13l941321390836.ps tmp/13l941321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/2oi5l1321390836.ps tmp/2oi5l1321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gvlu1321390836.ps tmp/3gvlu1321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/450yn1321390836.ps tmp/450yn1321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/5k28k1321390836.ps tmp/5k28k1321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/61nuh1321390836.ps tmp/61nuh1321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/77qb91321390836.ps tmp/77qb91321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/8td9x1321390836.ps tmp/8td9x1321390836.png",intern=TRUE))
character(0)
> try(system("convert tmp/9yi1n1321390836.ps tmp/9yi1n1321390836.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.612   0.493   3.244