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 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

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> y <- c(6.0,4.0,4.0,4.0,4.5,3.5,2.0,5.5,3.5,3.5,6.0,5.0,5.0,4.0,4.0,2.0,4.5,4.0,3.5,5.5,4.5,5.5,6.5,4.0,4.0,4.5,3.0,4.5,4.5,3.0,3.0,8.0,2.5,3.5,4.5,3.0,3.0,2.5,6.0,3.5,5.0,4.5,4.0,2.5,4.0,4.0,5.0,3.0,4.0,3.5,2.0,4.0,4.0,2.0,10.0,4.0,4.0,3.0,2.0,4.0,4.5,3.0,3.5,4.5,2.5,2.5,4.0,4.0,3.0,4.0,3.5,3.5,4.5,5.5,3.0,4.0,3.0,4.5,4.0,3.0,5.0,4.0,4.0,5.0,2.5,3.5,2.5,4.0,7.0,3.5,4.0,3.0,2.5,3.0,5.0,6.0,4.5,6.0,3.5,4.0,5.0,3.0,5.0,5.0,5.0,2.5,3.5,5.0,5.5,3.0,3.5,6.0,5.5,5.5,5.5,2.5,4.0,3.0,4.5,2.0,2.0,3.5,5.5,3.0,3.5,4.0,2.0,4.0,4.5,4.0,5.5,4.0,2.5,2.0,4.0,5.0,3.0,4.5,4.5,6.5,4.5,5.0,10.0,2.5,5.5,3.0,4.5,3.5,4.5,5.0,4.5,4.0,3.5,3.0,6.5,3.0,4.0,5.0,8.0)
> x <- c(5.3,5.6,3.8,4.0,4.0,3.6,4.4,3.6,4.0,3.8,5.1,6.7,5.1,4.0,3.3,2.7,4.7,3.3,4.4,6.9,6.0,7.6,4.7,6.9,4.2,3.6,4.4,4.7,4.9,3.8,5.3,5.6,5.8,5.6,3.8,7.1,7.3,2.9,7.1,5.6,6.4,4.9,4.0,3.8,4.4,3.3,4.4,7.3,6.4,5.1,5.8,4.0,4.4,2.4,6.2,5.8,4.9,3.8,2.7,3.1,3.8,4.7,4.2,4.0,2.2,6.4,6.9,4.2,2.0,4.4,6.2,4.2,6.7,6.4,5.8,5.1,2.9,4.7,4.2,6.2,5.1,4.0,4.7,4.4,5.1,4.7,4.7,3.3,6.2,4.2,5.8,2.2,3.6,4.9,4.2,6.9,6.9,6.4,4.2,4.9,5.1,3.3,4.4,4.0,5.1,5.6,4.7,5.3,5.6,3.8,2.9,6.2,4.7,5.6,2.0,3.6,4.2,3.8,5.6,4.4,6.4,3.1,4.9,3.3,4.2,4.4,3.3,4.4,4.0,7.3,4.9,3.6,3.8,3.6,4.7,5.8,4.0,4.0,3.8,4.9,6.7,6.7,5.3,4.7,4.7,6.4,6.9,4.4,3.6,4.9,4.4,6.2,8.4,4.9,4.4,3.8,6.2,4.9,6.9)
> 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 
-2.64490 -0.78293 -0.01229  0.70320  5.71978 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.52314    0.40091   6.293 2.96e-09 ***
x            0.33152    0.08082   4.102 6.56e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.29 on 157 degrees of freedom
Multiple R-squared: 0.0968,	Adjusted R-squared: 0.09105 
F-statistic: 16.83 on 1 and 157 DF,  p-value: 6.56e-05 

> postscript(file="/var/www/html/rcomp/tmp/1edtp1289749511.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/2pnas1289749511.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 
-1.159e-13  4.451e-16  6.846e-16  9.888e-16  2.173e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 2.523e+00  2.885e-15 8.745e+14   <2e-16 ***
x           3.315e-01  5.816e-16 5.700e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 9.287e-15 on 157 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 3.249e+29 on 1 and 157 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3iw9d1289749511.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-2.64490 -0.78293 -0.01229  0.70320  5.71978 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -3.335e-17  4.009e-01 -8.32e-17        1
x            6.953e-18  8.082e-02  8.60e-17        1

Residual standard error: 1.29 on 157 degrees of freedom
Multiple R-squared: 2.368e-34,	Adjusted R-squared: -0.006369 
F-statistic: 3.718e-32 on 1 and 157 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4iw9d1289749511.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-0.9270 -0.2640 -0.0319  0.2665  1.1947 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  4.113e+00  3.350e-02     122.8   <2e-16 ***
m$residuals -7.622e-16  2.613e-02 -2.92e-14        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.4225 on 157 degrees of freedom
Multiple R-squared: 9.105e-29,	Adjusted R-squared: -0.006369 
F-statistic: 1.429e-26 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/5tn8g1289749511.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 
-2.82106 -0.76247 -0.06189  0.65425  5.75697 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.01281    0.10196  -0.126     0.90
Residuals   -0.09535    0.08085  -1.179     0.24

Residual standard error: 1.281 on 156 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.008837,	Adjusted R-squared: 0.002483 
F-statistic: 1.391 on 1 and 156 DF,  p-value: 0.2401 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6lw8j1289749511.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7lw8j1289749511.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8eop41289749511.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9eop41289749511.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/10axmd1289749511.tab") 
> 
> try(system("convert tmp/1edtp1289749511.ps tmp/1edtp1289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pnas1289749511.ps tmp/2pnas1289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/3iw9d1289749511.ps tmp/3iw9d1289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/4iw9d1289749511.ps tmp/4iw9d1289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tn8g1289749511.ps tmp/5tn8g1289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/6lw8j1289749511.ps tmp/6lw8j1289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/7lw8j1289749511.ps tmp/7lw8j1289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/8eop41289749511.ps tmp/8eop41289749511.png",intern=TRUE))
character(0)
> try(system("convert tmp/9eop41289749511.ps tmp/9eop41289749511.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.871   1.403   3.838