R version 2.8.1 (2008-12-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(2.55,2.27,2.26,2.57,3.07,2.76,2.51,2.87,3.14,3.11,3.16,2.47,2.57,2.89,2.63,2.38,1.69,1.96,2.19,1.87,1.60,1.63,1.22,1.21,1.49,1.64,1.66,1.77,1.82,1.78,1.28,1.29,1.37,1.12,1.51,2.24,2.94,3.09,3.46,3.64,4.39,4.15,5.21,5.80,5.91,5.39,5.46,4.72,3.14,2.63,2.32,1.93,0.62,0.60,-0.37,-1.10,-1.68,-0.78)
> x <- c(-0.5348,-0.5591,-0.5200,-0.5173,-0.5153,-0.5048,-0.4950,-0.4597,-0.4681,-0.4909,-0.4579,-0.4758,-0.4662,-0.4821,-0.4767,-0.4740,-0.5295,-0.5075,-0.5222,-0.5377,-0.5108,-0.5197,-0.5292,-0.5024,-0.5175,-0.5088,-0.5180,-0.5177,-0.5027,-0.5002,-0.4882,-0.4603,-0.4687,-0.5092,-0.4729,-0.4488,-0.5085,-0.5142,-0.5130,-0.4721,-0.5425,-0.5123,-0.4845,-0.4950,-0.5024,-0.5349,-0.5861,-0.6495,-0.6751,-0.7095,-0.6941,-0.6794,-0.6559,-0.6051,-0.5713,-0.5532,-0.5341,-0.5315)
> 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 
-4.02914 -0.77701 -0.05206  0.68867  3.51042 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)  
(Intercept)    3.199      1.798   1.779   0.0807 .
x              1.591      3.398   0.468   0.6415  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.56 on 56 degrees of freedom
Multiple R-squared: 0.003899,	Adjusted R-squared: -0.01389 
F-statistic: 0.2192 on 1 and 56 DF,  p-value: 0.6415 

> postscript(file="/var/www/rcomp/tmp/13g511256675085.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/rcomp/tmp/2wzfd1256675085.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 
-1.640e-15 -1.396e-16  3.785e-17  1.846e-16  4.318e-16 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 3.199e+00  3.375e-16 9.477e+15   <2e-16 ***
x           1.591e+00  6.378e-16 2.495e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.927e-16 on 56 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 6.223e+30 on 1 and 56 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3ti261256675085.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-4.02914 -0.77701 -0.05206  0.68867  3.51042 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -7.848e-18  1.798e+00 -4.36e-18        1
x           -1.199e-17  3.398e+00 -3.53e-18        1

Residual standard error: 1.56 on 56 degrees of freedom
Multiple R-squared:     0,	Adjusted R-squared: -0.01786 
F-statistic:     0 on 1 and 56 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/49jsk1256675085.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.29236 -0.01411  0.02085  0.05868  0.12245 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 2.362e+00  1.281e-02    184.4   <2e-16 ***
m$residuals 2.136e-17  8.361e-03 2.55e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.09758 on 56 degrees of freedom
Multiple R-squared: 3.884e-29,	Adjusted R-squared: -0.01786 
F-statistic: 2.175e-27 on 1 and 56 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/rcomp/tmp/5rh971256675085.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 
-1.43769 -0.26339  0.06698  0.30352  1.10376 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.05757    0.06749  -0.853    0.397    
Residuals    0.98277    0.04532  21.684   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.5092 on 55 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8953,	Adjusted R-squared: 0.8934 
F-statistic: 470.2 on 1 and 55 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/6b4y71256675085.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/7n9221256675085.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/8xz701256675085.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/978es1256675085.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/10lfpm1256675085.tab") 
> 
> system("convert tmp/13g511256675085.ps tmp/13g511256675085.png")
> system("convert tmp/2wzfd1256675085.ps tmp/2wzfd1256675085.png")
> system("convert tmp/3ti261256675085.ps tmp/3ti261256675085.png")
> system("convert tmp/49jsk1256675085.ps tmp/49jsk1256675085.png")
> system("convert tmp/5rh971256675085.ps tmp/5rh971256675085.png")
> system("convert tmp/6b4y71256675085.ps tmp/6b4y71256675085.png")
> system("convert tmp/7n9221256675085.ps tmp/7n9221256675085.png")
> system("convert tmp/8xz701256675085.ps tmp/8xz701256675085.png")
> system("convert tmp/978es1256675085.ps tmp/978es1256675085.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.090   1.790   3.698