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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> y <- c(99.9,98.6,107.2,95.7,93.7,106.7,86.7,95.3,99.3,101.8,96,91.7,95.3,96.6,107.2,108,98.4,103.1,81.1,96.6,103.7,106.6,97.6,87.6,99.4,98.5,105.2,104.6,97.5,108.9,86.8,88.9,110.3,114.8,94.6,92,93.8,93.8,107.6,101,95.4,96.5,89.2,87.1,110.5,110.8,104.2,88.9,89.8,90,93.9,91.3,87.8,99.7,73.5,79.2,96.9,95.2,95.6,89.7)
> x <- c(98.8,100.5,110.4,96.4,101.9,106.2,81,94.7,101,109.4,102.3,90.7,96.2,96.1,106,103.1,102,104.7,86,92.1,106.9,112.6,101.7,92,97.4,97,105.4,102.7,98.1,104.5,87.4,89.9,109.8,111.7,98.6,96.9,95.1,97,112.7,102.9,97.4,111.4,87.4,96.8,114.1,110.3,103.9,101.6,94.6,95.9,104.7,102.8,98.1,113.9,80.9,95.7,113.2,105.9,108.8,102.3)
> 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 
-13.784  -3.387   1.176   3.580   9.089 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 16.33832    8.96028   1.823   0.0734 .  
x            0.80089    0.08875   9.024 1.21e-12 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.4 on 58 degrees of freedom
Multiple R-squared: 0.5841,	Adjusted R-squared: 0.5769 
F-statistic: 81.44 on 1 and 58 DF,  p-value: 1.208e-12 

> postscript(file="/var/www/html/rcomp/tmp/1p7gz1258377427.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/265zj1258377427.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 
-1.301e-13 -1.458e-15  1.973e-15  5.975e-15  1.011e-14 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.634e+01  3.011e-14 5.427e+14   <2e-16 ***
x           8.009e-01  2.982e-16 2.686e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.814e-14 on 58 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 7.213e+30 on 1 and 58 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3j1pb1258377427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-13.784  -3.387   1.176   3.580   9.089 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -1.240e-15  8.960e+00 -1.38e-16        1
x            1.460e-17  8.875e-02  1.64e-16        1

Residual standard error: 5.4 on 58 degrees of freedom
Multiple R-squared: 3.427e-33,	Adjusted R-squared: -0.01724 
F-statistic: 1.987e-31 on 1 and 58 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4o88s1258377427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-15.8243  -3.5907   0.7942   4.2180  10.7654 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  9.695e+01  8.261e-01     117.4   <2e-16 ***
m$residuals -2.376e-16  1.556e-01 -1.53e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 6.399 on 58 degrees of freedom
Multiple R-squared: 8.504e-31,	Adjusted R-squared: -0.01724 
F-statistic: 4.932e-29 on 1 and 58 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/57dzn1258377427.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 
-11.136115  -3.196977   0.007273   2.679851   8.846909 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  -0.1526     0.6004  -0.254      0.8    
Residuals     0.5334     0.1147   4.652    2e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4.61 on 57 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.2752,	Adjusted R-squared: 0.2625 
F-statistic: 21.64 on 1 and 57 DF,  p-value: 2.001e-05 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6b9j61258377427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7lvi81258377427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/86wr01258377427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9qif91258377427.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/10qs991258377427.tab") 
> 
> system("convert tmp/1p7gz1258377427.ps tmp/1p7gz1258377427.png")
> system("convert tmp/265zj1258377427.ps tmp/265zj1258377427.png")
> system("convert tmp/3j1pb1258377427.ps tmp/3j1pb1258377427.png")
> system("convert tmp/4o88s1258377427.ps tmp/4o88s1258377427.png")
> system("convert tmp/57dzn1258377427.ps tmp/57dzn1258377427.png")
> system("convert tmp/6b9j61258377427.ps tmp/6b9j61258377427.png")
> system("convert tmp/7lvi81258377427.ps tmp/7lvi81258377427.png")
> system("convert tmp/86wr01258377427.ps tmp/86wr01258377427.png")
> system("convert tmp/9qif91258377427.ps tmp/9qif91258377427.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.842   1.372   2.369