R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> y <- c(0.439620618,0.415578668,0.374927888,0.347499866,0.327363973,0.30912795,0.294782014,0.271568014,0.24362019,0.219233356,0.198928656,0.153201781,0.136500202,0.1247118,0.125838095,0.136887675,0.124547993,0.107159561,0.104998434,0.107308572,0.104528533,0.08088668,0.059476192,0.053914856,0.051123828,0.046363275,0.044694892,0.040634361,0.038625779,0.040071656,0.039128976,0.03841219,0.037037037,0.034563019,0.033502125,0.034427132,0.032522094,0.028919522,0.028209468,0.030091905,0.031718983,0.032220944,0.030558106,0.028205662,0.023910542)
> x <- c(65.2261159,66.18192324,68.51084108,70.33722683,71.143908,71.73414119,71.99927612,73.59456359,76.89891122,78.58059708,81.23539893,90.76678766,92.88460144,93.66937745,88.60410226,79.25341207,77.2465582,81.65647728,79.13140312,75.54106548,73.37597484,76.58704251,86.94640339,92.58089844,92.06547505,94.67242843,94.25869487,99.41227085,98.61304918,96.84902718,95.23722912,96.77880196,96.9227634,99.45702834,99.64352421,98.73290651,99.24435175,106.3037831,106.1372524,104.0509283,101.0545734,100,100.8805611,101.6755514,106.8457317)
> par1 = '0'
> par1 <- '0'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), Linear Regression Graphical Model Validation (v1.0.7) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_linear_regression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> 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 
-0.143035 -0.028056  0.004335  0.044591  0.124812 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.8529961  0.0653164   13.06  < 2e-16 ***
x           -0.0082511  0.0007327  -11.26 2.08e-14 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.061 on 43 degrees of freedom
Multiple R-squared: 0.7468,	Adjusted R-squared: 0.7409 
F-statistic: 126.8 on 1 and 43 DF,  p-value: 2.078e-14 

> postscript(file="/var/fisher/rcomp/tmp/1dcub1356030472.ps",horizontal=F,onefile=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/fisher/rcomp/tmp/2d3jn1356030472.ps",horizontal=F,onefile=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 
-4.050e-17 -6.796e-18 -4.290e-19  8.133e-18  3.217e-17 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  8.530e-01  1.413e-17  6.035e+16   <2e-16 ***
x           -8.251e-03  1.586e-19 -5.204e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.32e-17 on 43 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.708e+33 on 1 and 43 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/39pay1356030472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-0.143035 -0.028056  0.004335  0.044591  0.124812 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  6.593e-18  6.532e-02       0        1
x           -5.404e-20  7.327e-04       0        1

Residual standard error: 0.061 on 43 degrees of freedom
Multiple R-squared: 7.499e-33,	Adjusted R-squared: -0.02326 
F-statistic: 3.225e-31 on 1 and 43 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/4vmqr1356030472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.15320 -0.09048 -0.03550  0.09389  0.19021 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.246e-01  1.562e-02   7.978 5.09e-10 ***
m$residuals 4.099e-17  2.619e-01   0.000        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.1048 on 43 degrees of freedom
Multiple R-squared: 4.366e-32,	Adjusted R-squared: -0.02326 
F-statistic: 1.877e-30 on 1 and 43 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/fisher/rcomp/tmp/5h8x11356030472.ps",horizontal=F,onefile=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 
-0.063833 -0.007860 -0.001436  0.008091  0.056239 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.001790   0.003536  -0.506    0.615    
Residuals    0.877314   0.059143  14.834   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.02345 on 42 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8397,	Adjusted R-squared: 0.8359 
F-statistic:   220 on 1 and 42 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/6dfju1356030472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/7qbdr1356030472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/8r9gl1356030472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/9z1pt1356030472.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/10k5eb1356030472.tab") 
> 
> try(system("convert tmp/1dcub1356030472.ps tmp/1dcub1356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/2d3jn1356030472.ps tmp/2d3jn1356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/39pay1356030472.ps tmp/39pay1356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vmqr1356030472.ps tmp/4vmqr1356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/5h8x11356030472.ps tmp/5h8x11356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dfju1356030472.ps tmp/6dfju1356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qbdr1356030472.ps tmp/7qbdr1356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/8r9gl1356030472.ps tmp/8r9gl1356030472.png",intern=TRUE))
character(0)
> try(system("convert tmp/9z1pt1356030472.ps tmp/9z1pt1356030472.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  4.987   1.407   6.389