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(2.05,2.11,2.09,2.05,2.08,2.06,2.06,2.08,2.07,2.06,2.07,2.06,2.09,2.07,2.09,2.28,2.33,2.35,2.52,2.63,2.58,2.70,2.81,2.97,3.04,3.28,3.33,3.50,3.56,3.57,3.69,3.82,3.79,3.96,4.06,4.05,4.03,3.94,4.02,3.88,4.02,4.03,4.09,3.99,4.01,4.01,4.19,4.30,4.27,3.82,3.15,2.49,1.81,1.26,1.06,0.84,0.78,0.70,0.36,0.35)
> x <- c(1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.00,1.25,1.25,1.25,1.50,1.50,1.50,1.75,1.75,2.00,2.00,2.25,2.25,2.50,2.50,2.50,2.75,2.75,2.75,3.00,3.00,3.00,3.00,3.00,3.00,3.00,3.00,3.00,3.00,3.00,3.00,3.00,3.25,3.25,3.25,3.25,2.75,2.00,1.00,1.00,0.50,0.25,0.25,0.25,0.25,0.25)
> 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 
-0.70570 -0.05494  0.04116  0.19626  0.24626 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.78635    0.06706   11.73   <2e-16 ***
x            1.07739    0.03188   33.80   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.2434 on 58 degrees of freedom
Multiple R-squared: 0.9517,	Adjusted R-squared: 0.9508 
F-statistic:  1142 on 1 and 58 DF,  p-value: < 2.2e-16 

> postscript(file="/var/www/html/rcomp/tmp/1w9q51258735217.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/27nmu1258735217.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 
-3.731e-16 -1.004e-16 -6.238e-17  1.083e-16  1.927e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 7.864e-01  8.625e-17 9.117e+15   <2e-16 ***
x           1.077e+00  4.100e-17 2.628e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.131e-16 on 58 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 6.904e+32 on 1 and 58 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/31n2l1258735217.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.70570 -0.05494  0.04116  0.19626  0.24626 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept)  2.337e-16  6.706e-02  3.48e-15        1
x           -1.200e-16  3.188e-02 -3.76e-15        1

Residual standard error: 0.2434 on 58 degrees of freedom
Multiple R-squared: 1.51e-31,	Adjusted R-squared: -0.01724 
F-statistic: 8.755e-30 on 1 and 58 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4nb7k1258735217.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-1.7328 -0.9248 -0.1167  1.2300  1.4994 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 2.789e+00  1.394e-01    20.00   <2e-16 ***
m$residuals 5.989e-17  5.827e-01 1.03e-16        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.08 on 58 degrees of freedom
Multiple R-squared: 3.148e-31,	Adjusted R-squared: -0.01724 
F-statistic: 1.826e-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/58mf01258735217.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 
-0.54296 -0.07194  0.02394  0.07363  0.35554 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.01365    0.01850  -0.738    0.464    
Residuals    0.87699    0.08290  10.579 4.59e-15 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.1419 on 57 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.6626,	Adjusted R-squared: 0.6566 
F-statistic: 111.9 on 1 and 57 DF,  p-value: 4.589e-15 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6sapg1258735217.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7gc781258735217.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8hjzm1258735217.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9bk8z1258735217.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/10hjbc1258735217.tab") 
> 
> system("convert tmp/1w9q51258735217.ps tmp/1w9q51258735217.png")
> system("convert tmp/27nmu1258735217.ps tmp/27nmu1258735217.png")
> system("convert tmp/31n2l1258735217.ps tmp/31n2l1258735217.png")
> system("convert tmp/4nb7k1258735217.ps tmp/4nb7k1258735217.png")
> system("convert tmp/58mf01258735217.ps tmp/58mf01258735217.png")
> system("convert tmp/6sapg1258735217.ps tmp/6sapg1258735217.png")
> system("convert tmp/7gc781258735217.ps tmp/7gc781258735217.png")
> system("convert tmp/8hjzm1258735217.ps tmp/8hjzm1258735217.png")
> system("convert tmp/9bk8z1258735217.ps tmp/9bk8z1258735217.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.860   1.394   3.161