R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(3.192804132,3.192804132,3.192804132,3.192804132,3.214554929,3.246250589,3.235805662,3.181733746,3.088046927,3.050312455,3.07563914,3.235805662,3.286888614,3.286888614,3.225241362,3.17052917,3.181733746,3.203743505,3.214554929,3.203743505,3.17052917,3.159187111,3.136076753,3.214554929,3.225241362,3.225241362,3.203743505,3.192804132,3.203743505,3.225241362,3.225241362,3.214554929,3.203743505,3.181733746,3.147704154,3.17052917,3.159187111,3.159187111,3.147704154,3.136076753,3.136076753,3.147704154,3.147704154,3.136076753,3.147704154,3.112373757,3.050312455,3.088046927,3.063062535,3.024272248,3.024272248,3.024272248,3.050312455,3.063062535,3.037384045,2.997477149,2.941437798,2.897059699,2.955769344,3.112373757,3.136076753,3.088046927,3.010971786,2.969882079,3.010971786,3.112373757,3.147704154,3.147704154,3.112373757,3.063062535,3.07563914,3.159187111,3.181733746)
> x <- c(3.088046927,3.100290366,3.136076753,3.136076753,3.159187111,3.17052917,3.147704154,3.088046927,2.997477149,2.955769344,2.969882079,3.100290366,3.147704154,3.159187111,3.112373757,3.088046927,3.100290366,3.124301228,3.124301228,3.124301228,3.088046927,3.088046927,3.037384045,3.088046927,3.088046927,3.100290366,3.112373757,3.112373757,3.136076753,3.159187111,3.17052917,3.17052917,3.17052917,3.136076753,3.063062535,3.010971786,2.969882079,2.983782585,3.010971786,3.024272248,3.037384045,3.050312455,3.037384045,3.010971786,3.024272248,2.997477149,2.941437798,2.983782585,2.969882079,2.941437798,2.926880549,2.912090375,2.955769344,2.997477149,2.997477149,2.941437798,2.897059699,2.850443123,2.897059699,3.050312455,3.063062535,3.010971786,2.897059699,2.850443123,2.912090375,3.037384045,3.112373757,3.136076753,3.112373757,3.07563914,3.088046927,3.147704154,3.159187111)
> 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 
-0.093914 -0.016438  0.002822  0.015496  0.093668 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.49721    0.16041    3.10  0.00278 ** 
x            0.86479    0.05254   16.46  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.03837 on 71 degrees of freedom
Multiple R-squared: 0.7923,	Adjusted R-squared: 0.7894 
F-statistic: 270.9 on 1 and 71 DF,  p-value: < 2.2e-16 

> postscript(file="/var/www/html/rcomp/tmp/1mlc31256748789.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/29b9w1256748789.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 
-4.141e-16 -2.779e-16 -1.803e-16 -5.760e-17  1.237e-14 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 4.972e-01  6.205e-15 8.013e+13   <2e-16 ***
x           8.648e-01  2.033e-15 4.255e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.484e-15 on 71 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.81e+29 on 1 and 71 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/39mxw1256748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-0.093914 -0.016438  0.002822  0.015496  0.093668 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -1.206e-17  1.604e-01 -7.52e-17        1
x            4.751e-18  5.254e-02  9.04e-17        1

Residual standard error: 0.03837 on 71 degrees of freedom
Multiple R-squared: 1.248e-32,	Adjusted R-squared: -0.01408 
F-statistic: 8.858e-31 on 1 and 71 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/42nb41256748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.17403 -0.04688  0.02071  0.06280  0.10277 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 3.136e+00  8.772e-03    357.6   <2e-16 ***
m$residuals 3.091e-15  2.318e-01 1.33e-14        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.07494 on 71 degrees of freedom
Multiple R-squared: 1.126e-27,	Adjusted R-squared: -0.01408 
F-statistic: 7.995e-26 on 1 and 71 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/5baml1256748789.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 
-0.0299439 -0.0104929 -0.0009477  0.0115866  0.0689916 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.0009306  0.0021953  -0.424    0.673    
Residuals    0.8823902  0.0582496  15.148   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.01862 on 70 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.7663,	Adjusted R-squared: 0.7629 
F-statistic: 229.5 on 1 and 70 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6hipj1256748790.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7ytid1256748790.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8s2lz1256748790.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/91y431256748790.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/10vzar1256748790.tab") 
> 
> system("convert tmp/1mlc31256748789.ps tmp/1mlc31256748789.png")
> system("convert tmp/29b9w1256748789.ps tmp/29b9w1256748789.png")
> system("convert tmp/39mxw1256748789.ps tmp/39mxw1256748789.png")
> system("convert tmp/42nb41256748789.ps tmp/42nb41256748789.png")
> system("convert tmp/5baml1256748789.ps tmp/5baml1256748789.png")
> system("convert tmp/6hipj1256748790.ps tmp/6hipj1256748790.png")
> system("convert tmp/7ytid1256748790.ps tmp/7ytid1256748790.png")
> system("convert tmp/8s2lz1256748790.ps tmp/8s2lz1256748790.png")
> system("convert tmp/91y431256748790.ps tmp/91y431256748790.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.825   1.351   2.659