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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Type 'contributors()' for more information and
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> y <- c(3.43,3.57,4.29,2.71,3.14,3.14,3.57,3.29,2.43,3.00,2.71,2.71,2.14,2.29,3.29,3.86,3.14,2.00,3.14,3.29,3.29,3.00,2.71,2.57,2.86,3.29,3.57,2.71,3.43,3.14,3.57,3.71,4.14,4.57,3.57,4.14,4.00,2.43,4.00,4.14,3.71,3.57,2.00,3.57,3.71,2.86,2.57,4.57,3.57,3.57,3.29,3.00,2.86,2.14,4.29,3.43,3.71,3.43,3.14,2.00,3.43,3.43,3.43,3.43,2.71,4.43,3.14,3.86,2.71,3.57,2.86,3.00,3.86,3.29,3.57,2.86,3.00,3.14,3.29,3.57,3.57,2.43,2.71,3.57,2.71,2.86,3.71,3.29,3.86,2.43,2.43,2.71,2.43,3.14,3.00,4.57,3.00,3.00,2.57,2.57,3.29,2.71,2.86,3.00,2.86,2.43,2.57,2.71,3.14,2.14,2.00,2.57,3.43,5.00,4.14,3.00,3.57,2.86,3.14,1.86,3.71,2.43,3.57,2.86,2.71,3.00,3.14,3.43,3.00,3.71,3.43,2.29,3.29,2.57,2.29,3.71,2.71,3.00,3.00,3.14,3.29,4.14,3.00,3.00,3.29,3.86,3.57,3.00,1.43,2.86,3.71,3.43,4.14,2.71,3.43,2.71,3.43,3.14,2.43)
> x <- c(2.2,1.4,3.4,2,2.4,2.4,2.2,2.2,2.4,2.6,2.8,3.2,2.2,2,2.2,3,1.8,2.2,3.4,3.4,2.2,3.6,2.8,2,2.2,3,3,2.6,3.2,2.6,1.8,3.6,3.6,2.4,3.4,1.8,1.8,2.4,3.6,2.4,3.6,2.8,3,3.2,2,2.2,2.8,1.8,2.4,3.4,1,2.4,2.4,1.2,4.8,2.4,2.4,2.8,1.4,2.6,2.4,2.6,2.8,1.6,2.2,1.8,2.2,2.6,2,2.2,2.4,1.8,3,3.6,3,2.4,2.6,2.8,2,2.6,2.6,2.2,2.6,3.2,1.6,3.2,2.2,1.8,3.2,2.4,2.8,1.6,1.8,3,2.2,4.2,2.8,3.6,2.4,2.6,3,2.4,3.8,3,2.2,2.2,2,2.6,3,2.4,2.4,3.2,1.8,3.6,1.6,2.6,3.4,1.8,3,1.6,1.4,2.4,2.8,1.2,1.6,3.4,2,2.2,2.8,2.2,2.6,2.4,2.2,1.8,2.4,4,2.4,2.6,2.4,2.4,1.8,3,4.8,1.4,3.4,2.2,3.4,2.2,2.4,2.8,2.2,3.2,4.2,2.8,4,2.6,2.2,3,3.8)
> 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 
-1.69675 -0.41675 -0.02937  0.34587  1.61752 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.61529    0.18004   14.53  < 2e-16 ***
x            0.21311    0.06765    3.15  0.00196 ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.586 on 157 degrees of freedom
Multiple R-squared: 0.05944,	Adjusted R-squared: 0.05345 
F-statistic: 9.923 on 1 and 157 DF,  p-value: 0.001955 

> postscript(file="/var/www/html/rcomp/tmp/120f81290675740.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/220f81290675740.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 
-9.584e-16 -1.817e-16 -4.954e-17  6.790e-17  6.978e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 2.615e+00  1.777e-16 1.472e+16   <2e-16 ***
x           2.131e-01  6.675e-17 3.192e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.782e-16 on 157 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.019e+31 on 1 and 157 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3d9et1290675740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-1.69675 -0.41675 -0.02937  0.34587  1.61752 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)
(Intercept) 1.547e-17  1.800e-01 8.59e-17        1
x           1.282e-17  6.765e-02 1.89e-16        1

Residual standard error: 0.586 on 157 degrees of freedom
Multiple R-squared: 8.775e-33,	Adjusted R-squared: -0.006369 
F-statistic: 1.378e-30 on 1 and 157 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/460ve1290675740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.33481 -0.07908 -0.03646  0.09141  0.47500 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 3.163e+00  1.168e-02    270.8   <2e-16 ***
m$residuals 4.536e-17  2.006e-02 2.26e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.1473 on 157 degrees of freedom
Multiple R-squared: 5.603e-29,	Adjusted R-squared: -0.006369 
F-statistic: 8.796e-27 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/www/html/rcomp/tmp/5grdz1290675740.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 
-1.68032 -0.40761 -0.02391  0.34641  1.67538 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)  
(Intercept) -0.003181   0.046146  -0.069   0.9451  
Residuals    0.157461   0.079734   1.975   0.0501 .
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.58 on 156 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.02439,	Adjusted R-squared: 0.01814 
F-statistic:   3.9 on 1 and 156 DF,  p-value: 0.05005 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/69ic21290675740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/79ic21290675740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/89ic21290675740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/92st51290675740.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/10quuq1290675741.tab") 
> 
> try(system("convert tmp/120f81290675740.ps tmp/120f81290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/220f81290675740.ps tmp/220f81290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/3d9et1290675740.ps tmp/3d9et1290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/460ve1290675740.ps tmp/460ve1290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/5grdz1290675740.ps tmp/5grdz1290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/69ic21290675740.ps tmp/69ic21290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/79ic21290675740.ps tmp/79ic21290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/89ic21290675740.ps tmp/89ic21290675740.png",intern=TRUE))
character(0)
> try(system("convert tmp/92st51290675740.ps tmp/92st51290675740.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.967   1.498   4.827