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(0.96,0.95,0.95,0.96,0.96,0.96,0.95,0.96,0.96,0.96,0.95,0.95,0.96,0.96,0.96,0.96,0.96,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.96,0.96,0.96,0.97,0.97,0.97,0.96,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.95,0.94,0.94,0.94,0.93,0.93,0.93,0.93,0.92,0.93)
> x <- c(1.35,1.33,1.33,1.35,1.33,1.32,1.34,1.32,1.34,1.37,1.36,1.32,1.35,1.32,1.35,1.33,1.33,1.34,1.34,1.33,1.32,1.35,1.33,1.29,1.31,1.29,1.30,1.32,1.29,1.29,1.31,1.29,1.28,1.31,1.30,1.26,1.27,1.28,1.27,1.27,1.26,1.27,1.28,1.27,1.28,1.26,1.26,1.27,1.26,1.25,1.27,1.25,1.24,1.27,1.26)
> 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 
-0.0256159 -0.0057662  0.0008503  0.0043841  0.0226924 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.73077    0.04552  16.054  < 2e-16 ***
x            0.16917    0.03494   4.842 1.16e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.008811 on 53 degrees of freedom
Multiple R-squared: 0.3067,	Adjusted R-squared: 0.2936 
F-statistic: 23.44 on 1 and 53 DF,  p-value: 1.156e-05 

> postscript(file="/var/www/html/rcomp/tmp/1ij8o1289931552.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/2ta781289931552.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 
-3.105e-16 -1.511e-16 -1.059e-16  3.176e-17  3.505e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 7.308e-01  2.560e-15 2.854e+14   <2e-16 ***
x           1.692e-01  1.965e-15 8.608e+13   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4.956e-16 on 53 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 7.409e+27 on 1 and 53 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/34job1289931552.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
       Min         1Q     Median         3Q        Max 
-0.0256159 -0.0057662  0.0008503  0.0043841  0.0226924 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept)  3.705e-18  4.552e-02  8.14e-17        1
x           -3.440e-18  3.494e-02 -9.84e-17        1

Residual standard error: 0.008811 on 53 degrees of freedom
Multiple R-squared: 1.843e-32,	Adjusted R-squared: -0.01887 
F-statistic: 9.77e-31 on 1 and 53 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/44job1289931552.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
       Min         1Q     Median         3Q        Max 
-0.0105503 -0.0054751 -0.0003999  0.0046753  0.0114423 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 9.511e-01  7.902e-04     1204   <2e-16 ***
m$residuals 1.055e-15  9.136e-02 1.15e-14        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.00586 on 53 degrees of freedom
Multiple R-squared: 3.319e-28,	Adjusted R-squared: -0.01887 
F-statistic: 1.759e-26 on 1 and 53 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/5wtne1289931552.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 
-0.0173079 -0.0028003  0.0003709  0.0040933  0.0118663 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.0002138  0.0008019  -0.267    0.791    
Residuals    0.7679068  0.0941096   8.160 7.13e-11 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.00589 on 52 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.5615,	Adjusted R-squared: 0.553 
F-statistic: 66.58 on 1 and 52 DF,  p-value: 7.126e-11 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6724z1289931552.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7724z1289931552.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/80b421289931552.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/90b421289931552.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/10wl1t1289931552.tab") 
> 
> try(system("convert tmp/1ij8o1289931552.ps tmp/1ij8o1289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ta781289931552.ps tmp/2ta781289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/34job1289931552.ps tmp/34job1289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/44job1289931552.ps tmp/44job1289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/5wtne1289931552.ps tmp/5wtne1289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/6724z1289931552.ps tmp/6724z1289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/7724z1289931552.ps tmp/7724z1289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/80b421289931552.ps tmp/80b421289931552.png",intern=TRUE))
character(0)
> try(system("convert tmp/90b421289931552.ps tmp/90b421289931552.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.819   1.334   2.271