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(11,7,17,10,12,12,11,11,12,13,14,16,11,10,11,15,9,11,17,17,11,18,14,10,11,15,15,13,16,13,9,18,18,12,17,9,9,12,18,12,18,14,15,16,10,11,14,9,12,17,5,12,12,6,24,12,12,14,7,13,12,13,14,8,11,9,11,13,10,11,12,9,15,18,15,12,13,14,10,13,13,11,13,16,8,16,11,9,16,12,14,8,9,15,11,21,14,18,12,13,15,12,19,15,11,11,10,13,15,12,12,16,9,18,8,13,17,9,15,8,7,12,14,6,8,17,10,11,14,11,13,12,11,9,12,20,12,13,12,12,9,15,24,7,17,11,17,11,12,14,11,16,21,14,20,13,11,15,19)
> x <- c(14,11,6,12,8,10,10,11,16,11,13,12,8,12,11,4,9,8,8,14,15,16,9,14,11,8,9,9,9,9,10,16,11,8,9,16,11,16,12,12,14,9,10,9,10,12,14,14,10,14,16,9,10,6,8,13,10,8,7,15,9,10,12,13,10,11,8,9,13,11,8,9,9,15,9,10,14,12,12,11,14,6,12,8,14,11,10,14,12,10,14,5,11,10,9,10,16,13,9,10,10,7,9,8,14,14,8,9,14,14,8,8,8,7,6,8,6,11,14,11,11,11,14,8,20,11,8,11,10,14,11,9,9,8,10,13,13,12,8,13,14,12,14,15,13,16,9,9,9,8,7,16,11,9,11,9,14,13,16)
> 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 
-8.0265 -1.9595 -0.7584  2.1746 11.2416 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 12.49018    1.10373  11.316   <2e-16 ***
x            0.03352    0.09815   0.342    0.733    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.455 on 157 degrees of freedom
Multiple R-squared: 0.0007424,	Adjusted R-squared: -0.005622 
F-statistic: 0.1166 on 1 and 157 DF,  p-value: 0.7332 

> postscript(file="/var/wessaorg/rcomp/tmp/10sli1321400337.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/29icw1321400337.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 
-5.388e-15 -3.280e-16  7.750e-17  4.911e-16  1.165e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.249e+01  2.386e-16 5.235e+16   <2e-16 ***
x           3.352e-02  2.122e-17 1.580e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 7.468e-16 on 157 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.497e+30 on 1 and 157 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/30l461321400337.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-8.0265 -1.9595 -0.7584  2.1746 11.2416 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.251e-18  1.104e+00       0        1
x           -4.842e-18  9.815e-02       0        1

Residual standard error: 3.455 on 157 degrees of freedom
Multiple R-squared: 3.552e-34,	Adjusted R-squared: -0.006369 
F-statistic: 5.577e-32 on 1 and 157 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4gct91321400337.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-0.231075 -0.063461  0.003584  0.070630  0.305290 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.286e+01  7.469e-03    1721   <2e-16 ***
m$residuals -2.548e-17  2.175e-03       0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.09418 on 157 degrees of freedom
Multiple R-squared: 1.45e-28,	Adjusted R-squared: -0.006369 
F-statistic: 2.277e-26 on 1 and 157 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/5rs8h1321400337.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 
-7.4730 -2.2628 -0.4089  2.1081 11.3258 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)  
(Intercept)  0.007156   0.272870   0.026   0.9791  
Residuals   -0.138762   0.079991  -1.735   0.0848 .
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.43 on 156 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.01893,	Adjusted R-squared: 0.01264 
F-statistic: 3.009 on 1 and 156 DF,  p-value: 0.08477 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6ms7s1321400337.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7nm8j1321400337.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8ifei1321400337.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/98z0h1321400337.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/10idei1321400337.tab") 
> 
> try(system("convert tmp/10sli1321400337.ps tmp/10sli1321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/29icw1321400337.ps tmp/29icw1321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/30l461321400337.ps tmp/30l461321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/4gct91321400337.ps tmp/4gct91321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rs8h1321400337.ps tmp/5rs8h1321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ms7s1321400337.ps tmp/6ms7s1321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nm8j1321400337.ps tmp/7nm8j1321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ifei1321400337.ps tmp/8ifei1321400337.png",intern=TRUE))
character(0)
> try(system("convert tmp/98z0h1321400337.ps tmp/98z0h1321400337.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.651   0.459   3.117