R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(103,102.4,102,101.8,101.6,101.4,101.3,101.4,101.7,102.4,103.1,103.8,104.4,105,105.7,106.4,107.1,107.9,108.8,109.6,110.3,110.8,111.2,111.7,112.3,112.8,113.1,113.1,113.1,113.2,113.1,112.8,112.5,112.3,112.5,112.9,113.5,114.1,114.6,114.9,115.4,115.7,116.1,116.5,117.1,117.5,117.7,117.7,117.7,117.6,117.5,117.6,117.9,118.2,118.5,118.7,118.8,118.9,119,119)
> x <- c(101.1,100.7,100,100,100.8,101.9,102.7,103.1,103.5,103.9,104.4,105.2,106,107,108.2,109,109.1,109.3,110.1,110.7,110.8,110.7,110.9,111.3,111.6,111.8,112.1,112.3,112.5,113,113.6,114.4,114.9,115.2,116,117,118,119.4,121.1,123.1,125,126.3,127.4,129,131,133.3,135.9,138.4,140.3,141.7,143.1,144.5,146,147.7,149,149.7,150.2,150.5,150.7,150.9)
> par1 = '0'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> 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 
-4.65201 -2.41009  0.06572  2.38057  4.14965 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 72.85003    2.70386   26.94   <2e-16 ***
x            0.32204    0.02234   14.42   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.801 on 58 degrees of freedom
Multiple R-squared: 0.7818,	Adjusted R-squared: 0.778 
F-statistic: 207.8 on 1 and 58 DF,  p-value: < 2.2e-16 

> postscript(file="/var/www/html/rcomp/tmp/17tb61229957432.ps",horizontal=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/www/html/rcomp/tmp/26r6q1229957432.ps",horizontal=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 
-7.057e-15 -3.540e-15  6.266e-16  3.096e-15  8.468e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 7.285e+01  4.122e-15 1.767e+16   <2e-16 ***
x           3.220e-01  3.406e-17 9.456e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4.269e-15 on 58 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 8.942e+31 on 1 and 58 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3epmx1229957432.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-4.65201 -2.41009  0.06572  2.38057  4.14965 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept)  9.428e-16  2.704e+00  3.49e-16        1
x           -6.324e-18  2.234e-02 -2.83e-16        1

Residual standard error: 2.801 on 58 degrees of freedom
Multiple R-squared: 2.422e-33,	Adjusted R-squared: -0.01724 
F-statistic: 1.405e-31 on 1 and 58 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4k0ag1229957432.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
   Min     1Q Median     3Q    Max 
-6.425 -3.591 -2.142  3.744  9.967 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  1.115e+02  6.844e-01     162.9   <2e-16 ***
m$residuals -3.944e-16  2.485e-01 -1.59e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.301 on 58 degrees of freedom
Multiple R-squared: 1.177e-29,	Adjusted R-squared: -0.01724 
F-statistic: 6.827e-28 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/www/html/rcomp/tmp/509x21229957432.ps",horizontal=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 
-0.79435 -0.26851 -0.02462  0.30771  0.72726 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.000233   0.051259  -0.005    0.996    
Residuals    0.990317   0.018583  53.291   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.3937 on 57 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.9803,	Adjusted R-squared:  0.98 
F-statistic:  2840 on 1 and 57 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6zxu81229957432.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7he881229957432.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8yvfn1229957432.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9bl111229957432.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/www/html/rcomp/tmp/10kor81229957432.tab") 
> 
> system("convert tmp/17tb61229957432.ps tmp/17tb61229957432.png")
> system("convert tmp/26r6q1229957432.ps tmp/26r6q1229957432.png")
> system("convert tmp/3epmx1229957432.ps tmp/3epmx1229957432.png")
> system("convert tmp/4k0ag1229957432.ps tmp/4k0ag1229957432.png")
> system("convert tmp/509x21229957432.ps tmp/509x21229957432.png")
> system("convert tmp/6zxu81229957432.ps tmp/6zxu81229957432.png")
> system("convert tmp/7he881229957432.ps tmp/7he881229957432.png")
> system("convert tmp/8yvfn1229957432.ps tmp/8yvfn1229957432.png")
> system("convert tmp/9bl111229957432.ps tmp/9bl111229957432.png")
> 
> 
> proc.time()
   user  system elapsed 
  3.836   2.414   4.156