R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(17203555.19,19542066.35,17332692.2,17962530.06,18664899.14,15878594.85,16014583.21,16867867.15,16014007.43,16793894.2,16127590.29,13557713.21,14238232.92,15465943.69,13881008.13,14346884.11,15668789.39,14521120.61,15071819.75,15816786.32,17180395.07,20432335.71,21289464.94,18203628.31,20159479.84,21053177.29,19673603.19,21473302.24,20244720.94,19049596.62,20194317.23,18021889.62,19537280.81,20286602.27,17967742.04,16409869.75,17802737.97,18509941.2,18161267.85,16721314.25,19106861.48,16772112.17,17463628.82,16162288.88,17862884.98,17664893.45,17180794.3,15672722.75,15189796.81,17699369.88,17444615.98,15930700.75,19691579.52,16697955.94,16896235.55,17972385.83,17637387.4,15213975.95,16471559.62,14731798.37)
> x <- c(17681170.13,19858875.65,16997477.78,16969881.42,18908869.11,15692144.17,15159951.13,15806842.33,16007123.26,16059123.25,16189383.57,12522497.94,14733828.17,15686348.94,13779681.49,14423755.53,15290621.44,14308336.46,13855616.12,14384486.00,15638580.70,19711553.27,20359793.22,16141449.72,20056915.06,20605542.58,19325754.03,20547653.75,19211178.55,19009453.59,18746813.27,16471529.53,18957217.20,20515191.95,18374420.60,16192909.22,18147463.68,19301440.71,18344657.85,17183629.01,19629987.60,17167191.42,17428458.32,16016524.60,18466459.42,18406552.23,18174068.44,14851949.20,16260733.42,18329610.38,18003781.65,15903762.33,19554176.37,16554237.93,16198892.67,16571771.60,17535166.38,16198106.13,17487530.67,13768040.14)
> 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 
-1375030  -521914  -131644   467584  1746814 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.841e+06  8.229e+05   2.237   0.0292 *  
x           9.055e-01  4.764e-02  19.008   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 728000 on 58 degrees of freedom
Multiple R-squared: 0.8617,	Adjusted R-squared: 0.8593 
F-statistic: 361.3 on 1 and 58 DF,  p-value: < 2.2e-16 

> postscript(file="/var/www/rcomp/tmp/1nkvd1289743465.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/rcomp/tmp/2gtuy1289743465.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 
-2.041e-09 -7.707e-10 -1.088e-10  4.326e-10  9.769e-09 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.841e+06  1.770e-09 1.040e+15   <2e-16 ***
x           9.055e-01  1.024e-16 8.839e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.565e-09 on 58 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 7.814e+31 on 1 and 58 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3r3u11289743465.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-1375030  -521914  -131644   467584  1746814 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept)  7.262e-11  8.229e+05  8.82e-17        1
x           -3.881e-18  4.764e-02 -8.15e-17        1

Residual standard error: 728000 on 58 degrees of freedom
Multiple R-squared: 6.7e-34,	Adjusted R-squared: -0.01724 
F-statistic: 3.886e-32 on 1 and 58 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/4r3u11289743465.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-4200269 -1160466   -71325  1472551  3118950 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  1.738e+07  2.346e+05      74.1   <2e-16 ***
m$residuals -4.888e-16  3.277e-01 -1.49e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1817000 on 58 degrees of freedom
Multiple R-squared: 2.61e-30,	Adjusted R-squared: -0.01724 
F-statistic: 1.514e-28 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/rcomp/tmp/51ut41289743465.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 
-1580112  -485422   -37970   500404  1365882 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.455e+04  8.229e+04   0.177     0.86    
Residuals   4.968e-01  1.143e-01   4.344 5.81e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 632000 on 57 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.2488,	Adjusted R-squared: 0.2356 
F-statistic: 18.87 on 1 and 57 DF,  p-value: 5.807e-05 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/6u3s71289743465.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/7u3s71289743465.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/8nc9a1289743465.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/9nc9a1289743465.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/1014701289743465.tab") 
> 
> try(system("convert tmp/1nkvd1289743465.ps tmp/1nkvd1289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gtuy1289743465.ps tmp/2gtuy1289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/3r3u11289743465.ps tmp/3r3u11289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/4r3u11289743465.ps tmp/4r3u11289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/51ut41289743465.ps tmp/51ut41289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/6u3s71289743465.ps tmp/6u3s71289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/7u3s71289743465.ps tmp/7u3s71289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nc9a1289743465.ps tmp/8nc9a1289743465.png",intern=TRUE))
character(0)
> try(system("convert tmp/9nc9a1289743465.ps tmp/9nc9a1289743465.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.890   1.030   3.932