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

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> y <- 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)
> x <- c(7,5.5,3,6,4,5,5,5.5,8,5.5,6.5,6,4,6,5.5,2,4.5,4,4,7,7.5,8,4.5,7,5.5,4,4.5,4.5,4.5,4.5,5,8,5.5,4,4.5,8,5.5,8,6,6,7,4.5,5,4.5,5,6,7,7,5,7,8,4.5,5,3,4,6.5,5,4,3.5,7.5,4.5,5,6,6.5,5,5.5,4,4.5,6.5,5.5,4,4.5,4.5,7.5,4.5,5,7,6,6,5.5,7,3,6,4,7,5.5,5,7,6,5,7,2.5,5.5,5,4.5,5,8,6.5,4.5,5,5,3.5,4.5,4,7,7,4,4.5,7,7,4,4,4,3.5,3,4,3,5.5,7,5.5,5.5,5.5,7,4,10,5.5,4,5.5,5,7,5.5,4.5,4.5,4,5,6.5,6.5,6,4,6.5,7,6,7,7.5,6.5,8,4.5,4.5,4.5,4,3.5,8,5.5,4.5,5.5,4.5,7,6.5,8)
> 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 
-3.1739 -0.6776 -0.1154  0.6261  3.5846 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   2.8435     0.3739   7.605 2.45e-12 ***
x             0.3585     0.0665   5.391 2.53e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.171 on 157 degrees of freedom
Multiple R-squared: 0.1562,	Adjusted R-squared: 0.1508 
F-statistic: 29.06 on 1 and 157 DF,  p-value: 2.528e-07 

> postscript(file="/var/www/html/rcomp/tmp/1zaso1289936815.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/2rja91289936815.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 
-1.086e-14 -2.872e-16 -4.239e-17  1.191e-16  2.329e-14 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 2.844e+00  6.646e-16 4.278e+15   <2e-16 ***
x           3.585e-01  1.182e-16 3.033e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.081e-15 on 157 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 9.199e+30 on 1 and 157 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3rja91289936815.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-3.1739 -0.6776 -0.1154  0.6261  3.5846 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept)  3.367e-16  3.739e-01  9.00e-16        1
x           -5.677e-17  6.650e-02 -8.54e-16        1

Residual standard error: 1.171 on 157 degrees of freedom
Multiple R-squared: 5.073e-33,	Adjusted R-squared: -0.006369 
F-statistic: 7.965e-31 on 1 and 157 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/42tru1289936815.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-1.23565 -0.33935  0.01917  0.37769  1.63251 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  4.796e+00  3.994e-02     120.1   <2e-16 ***
m$residuals -2.082e-17  3.434e-02 -6.06e-16        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.5036 on 157 degrees of freedom
Multiple R-squared: 7.528e-31,	Adjusted R-squared: -0.006369 
F-statistic: 1.182e-28 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/5c2qf1289936815.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 
-3.1477 -0.7040 -0.1472  0.6255  3.5315 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.001136   0.092897   0.012    0.990
Residuals   0.106344   0.079877   1.331    0.185

Residual standard error: 1.168 on 156 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.01123,	Adjusted R-squared: 0.004896 
F-statistic: 1.772 on 1 and 156 DF,  p-value: 0.185 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/65t701289936815.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/75t701289936815.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8ykpl1289936815.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9ykpl1289936815.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/10cc4u1289936815.tab") 
> 
> try(system("convert tmp/1zaso1289936815.ps tmp/1zaso1289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rja91289936815.ps tmp/2rja91289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/3rja91289936815.ps tmp/3rja91289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/42tru1289936815.ps tmp/42tru1289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/5c2qf1289936815.ps tmp/5c2qf1289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/65t701289936815.ps tmp/65t701289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/75t701289936815.ps tmp/75t701289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ykpl1289936815.ps tmp/8ykpl1289936815.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ykpl1289936815.ps tmp/9ykpl1289936815.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.868   1.402   2.346