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.

Type 'demo()' for some demos, 'help()' for on-line help, or
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> y <- c(6.9,7.1,8.6,5.4,6.3,6.3,7.1,6.6,4.9,6.0,5.4,5.4,4.3,4.6,6.6,7.7,6.3,4.0,6.3,6.6,6.6,6.0,5.4,5.1,5.7,6.6,7.1,5.4,6.9,6.3,7.1,7.4,8.3,9.1,7.1,8.3,8.0,4.9,8.0,8.3,7.4,7.1,4.0,7.1,7.4,5.7,5.1,9.1,7.1,7.1,6.6,6.0,5.7,4.3,8.6,6.9,7.4,6.9,6.3,4.0,6.9,6.9,6.9,6.9,5.4,8.9,6.3,7.7,5.4,7.1,5.7,6.0,7.7,6.6,7.1,5.7,6.0,6.3,6.6,7.1,7.1,4.9,5.4,7.1,5.4,5.7,7.4,6.6,7.7,4.9,4.9,5.4,4.9,6.3,6.0,9.1,6.0,6.0,5.1,5.1,6.6,5.4,5.7,6.0,5.7,4.9,5.1,5.4,6.3,4.3,4.0,5.1,6.9,10.0,8.3,6.0,7.1,5.7,6.3,3.7,7.4,4.9,7.1,5.7,5.4,6.0,6.3,6.9,6.0,7.4,6.9,4.6,6.6,5.1,4.6,7.4,5.4,6.0,6.0,6.3,6.6,8.3,6.0,6.0,6.6,7.7,7.1,6.0,2.9,5.7,7.4,6.9,8.3,5.4,6.9,5.4,6.9,6.3,4.9)
> x <- c(8.7,7.7,8.3,7.7,6.3,9.7,8.3,7.0,7.3,8.3,8.0,6.0,7.3,5.0,7.3,9.3,6.7,4.0,8.0,6.7,7.0,6.7,7.0,7.7,9.3,8.0,8.0,8.0,7.7,7.7,9.7,8.0,6.0,8.3,7.0,8.7,7.3,7.3,7.3,7.7,10.0,7.7,5.7,7.7,7.7,8.3,8.0,8.0,7.7,7.0,8.0,8.0,9.3,5.3,6.7,9.7,9.0,7.3,9.3,5.3,8.3,8.0,9.3,8.0,7.7,10.0,8.0,7.0,8.3,8.3,7.3,7.7,8.7,7.7,8.3,7.0,8.3,8.0,9.7,7.3,9.0,8.7,7.3,8.0,9.0,8.0,8.0,9.7,7.3,7.0,8.0,8.0,7.7,6.7,9.0,8.7,8.3,7.0,7.0,6.3,7.0,7.0,5.3,7.3,9.7,5.0,5.7,5.0,7.0,7.0,6.3,8.0,6.7,5.7,7.7,8.0,4.7,6.3,8.0,4.3,7.3,5.3,6.3,8.3,8.3,7.7,8.0,8.7,8.7,8.3,6.0,7.0,8.7,7.7,7.7,7.3,6.7,4.3,8.0,5.0,4.7,7.3,3.3,8.0,7.3,8.0,6.3,6.7,4.3,6.7,7.3,8.0,9.7,4.0,6.7,7.0,8.0,7.3,6.7)
> 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 
-2.4016 -0.8198 -0.0834  0.6946  4.2424 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  3.90073    0.51968   7.506 4.28e-12 ***
x            0.32577    0.06877   4.737 4.82e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.128 on 157 degrees of freedom
Multiple R-squared: 0.1251,	Adjusted R-squared: 0.1195 
F-statistic: 22.44 on 1 and 157 DF,  p-value: 4.817e-06 

> postscript(file="/var/www/html/rcomp/tmp/1xmrw1289936921.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/2xmrw1289936921.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 
-1.386e-13  4.433e-16  9.380e-16  1.591e-15  6.892e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 3.901e+00  5.135e-15 7.597e+14   <2e-16 ***
x           3.258e-01  6.795e-16 4.794e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.115e-14 on 157 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.299e+29 on 1 and 157 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/38dqy1289936921.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-2.4016 -0.8198 -0.0834  0.6946  4.2424 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -8.321e-18  5.197e-01 -1.60e-17        1
x            1.354e-17  6.877e-02  1.97e-16        1

Residual standard error: 1.128 on 157 degrees of freedom
Multiple R-squared: 1.924e-32,	Adjusted R-squared: -0.006369 
F-statistic: 3.02e-30 on 1 and 157 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4057j1289936921.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-1.35001 -0.14465  0.08339  0.22999  0.83266 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  6.326e+00  3.382e-02     187.0   <2e-16 ***
m$residuals -1.168e-16  3.017e-02 -3.87e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.4265 on 157 degrees of freedom
Multiple R-squared: 3.207e-28,	Adjusted R-squared: -0.006369 
F-statistic: 5.035e-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/5be641289936921.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 
-2.38815 -0.85406 -0.03962  0.72465  4.13339 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)  
(Intercept) -0.002063   0.089193  -0.023   0.9816  
Residuals    0.135982   0.079601   1.708   0.0896 .
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.121 on 156 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.01836,	Adjusted R-squared: 0.01207 
F-statistic: 2.918 on 1 and 156 DF,  p-value: 0.08957 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6be641289936921.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/74n671289936921.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/84n671289936921.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/94n671289936921.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/10bol11289936921.tab") 
> 
> try(system("convert tmp/1xmrw1289936921.ps tmp/1xmrw1289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xmrw1289936921.ps tmp/2xmrw1289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/38dqy1289936921.ps tmp/38dqy1289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/4057j1289936921.ps tmp/4057j1289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/5be641289936921.ps tmp/5be641289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/6be641289936921.ps tmp/6be641289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/74n671289936921.ps tmp/74n671289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/84n671289936921.ps tmp/84n671289936921.png",intern=TRUE))
character(0)
> try(system("convert tmp/94n671289936921.ps tmp/94n671289936921.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.889   1.427   2.469