R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> y <- c(57619,57077,56161,55614,57029,57667,57275,57514,58519,58759,58170,58277,61050,63191,64035,63358,62149,61789,60973,61229,60566,61922,62945,64810,66641,67675,66585,66573,66193,65545,64835,67184,69421,72359,74730,75067,74927,74845,75335,78121,79944,82779,81484,79939,80611,79088,79992,77800,76277,75425,74524,72844,70768,70172,67726,68032,67096,68261,67363,67322,57465,57031,54046,47435,43623,48866,53075,53778,51237,50393,49947,50660,50307,52235,51783,51602,47498,45981,43588,42791,41325,38917,36971,33628,31445,28478,19247,12209,10467,10127,10344,10117,8142,6404,4519,3482,2373,1772,1178,746,503,293,161,91,55,20,14,8,2,0,1)
> x <- c(60747,60194,58401,58280,59246,60363,59486,60288,61064,61128,60793,61681,63587,65952,66995,66366,65038,64644,63404,63654,61635,62560,63514,65319,67256,67334,67931,66922,66512,66495,65767,68454,71116,73792,75737,77046,76729,76567,78036,80147,82512,84873,83387,81732,81449,80647,80680,79230,77543,75689,74454,73085,71606,71043,67799,67936,67596,67730,66928,66809,55559,55167,51834,45337,40839,44921,47745,48088,45971,43752,42504,42367,41333,41358,40150,38294,34220,31910,29516,27291,25732,23261,20671,18158,16021,13587,8757,4977,4025,3711,3613,3241,2300,1659,1085,807,470,296,190,102,89,37,16,4,0,2,2,0,0,0,0)
> 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 
-6380.4 -3074.4  -559.3   685.6 11866.7 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 6.380e+03  8.574e+02   7.441 2.44e-11 ***
x           9.058e-01  1.575e-02  57.512  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4741 on 109 degrees of freedom
Multiple R-squared: 0.9681,	Adjusted R-squared: 0.9678 
F-statistic:  3308 on 1 and 109 DF,  p-value: < 2.2e-16 

> postscript(file="/var/www/rcomp/tmp/18s6a1291824107.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/www/rcomp/tmp/28s6a1291824107.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 
-3.645e-11 -2.335e-12  5.050e-13  2.550e-12  1.574e-11 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 6.380e+03  9.090e-13 7.019e+15   <2e-16 ***
x           9.058e-01  1.670e-17 5.425e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.026e-12 on 109 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.943e+33 on 1 and 109 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/31k5v1291824107.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-6380.4 -3074.4  -559.3   685.6 11866.7 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  8.460e-16  8.574e+02       0        1
x           -5.990e-19  1.575e-02       0        1

Residual standard error: 4741 on 109 degrees of freedom
Multiple R-squared: 1.144e-34,	Adjusted R-squared: -0.009174 
F-statistic: 1.247e-32 on 1 and 109 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/4ct5y1291824107.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
   Min     1Q Median     3Q    Max 
-41976 -24390  12548  19134  34902 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  4.836e+04  2.479e+03   19.51   <2e-16 ***
m$residuals -1.367e-16  5.276e-01    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 26110 on 109 degrees of freedom
Multiple R-squared: 2.065e-32,	Adjusted R-squared: -0.009174 
F-statistic: 2.251e-30 on 1 and 109 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/542mj1291824107.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 
-4718.2  -366.3   -23.8   495.5  2004.4 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -22.89436   83.48827  -0.274    0.784    
Residuals     0.98827    0.01784  55.393   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 875.6 on 108 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.966,	Adjusted R-squared: 0.9657 
F-statistic:  3068 on 1 and 108 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/642mj1291824107.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/7fbl41291824107.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/8fbl41291824107.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/9qlk71291824107.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/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/104uif1291824107.tab") 
> 
> try(system("convert tmp/18s6a1291824107.ps tmp/18s6a1291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/28s6a1291824107.ps tmp/28s6a1291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/31k5v1291824107.ps tmp/31k5v1291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ct5y1291824107.ps tmp/4ct5y1291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/542mj1291824107.ps tmp/542mj1291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/642mj1291824107.ps tmp/642mj1291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/7fbl41291824107.ps tmp/7fbl41291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/8fbl41291824107.ps tmp/8fbl41291824107.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qlk71291824107.ps tmp/9qlk71291824107.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.300   1.580   3.806