R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> y <- c(127800,127700,128500,129400,128800,128800,131300,131100,131500,132900,133500,133400,134828,136488,135943,138717,139223,139869,140507,140259,139220,144033,144683,147354,148813,152657,155912,155271,161382,162106,164825,162810,163398,164844,165910,165774,164881,164861,165501,164334,162229,162748,163915,160890,159779,161106,160659,160007,158917,159052,159507,159107,159925,161327,159957,156997,159316,159793,161383,161828,162887,164071,163810,166708,168481,169913,169602,170559,170943)
> x <- c(138900,136400,133900,130400,133200,132500,130400,132000,131400,133300,129700,129500,134257,133802,134542,132423,135853,135676,137311,139515,138554,139560,136171,137454,142388,143616,140197,148011,152637,152341,159219,161478,163350,166044,160925,163439,165411,160522,159302,151933,156735,156254,158051,157038,154626,153093,147274,150847,157165,157384,152655,154088,156583,156608,159543,162916,167167,172470,167473,164832,174144,177945,180962,179105,185076,183863,189329,191268,190450)
> par1 = '0'
> 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 
-15262.2  -5194.0    357.4   5694.4  12020.0 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 4.446e+04  7.478e+03   5.945  1.1e-07 ***
x           7.099e-01  4.870e-02  14.578  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 6820 on 67 degrees of freedom
Multiple R-squared: 0.7603,	Adjusted R-squared: 0.7567 
F-statistic: 212.5 on 1 and 67 DF,  p-value: < 2.2e-16 

> postscript(file="/var/wessaorg/rcomp/tmp/1vdjq1321379289.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/wessaorg/rcomp/tmp/2m7il1321379289.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 
-9.670e-11 -5.078e-12 -4.810e-13  8.478e-12  1.476e-11 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 4.446e+04  1.608e-11 2.765e+15   <2e-16 ***
x           7.099e-01  1.047e-16 6.780e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.466e-11 on 67 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 4.597e+31 on 1 and 67 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3c6r61321379289.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-15262.2  -5194.0    357.4   5694.4  12020.0 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.342e-12  7.478e+03       0        1
x            1.598e-17  4.870e-02       0        1

Residual standard error: 6820 on 67 degrees of freedom
Multiple R-squared: 2.399e-33,	Adjusted R-squared: -0.01493 
F-statistic: 1.607e-31 on 1 and 67 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4mv861321379289.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-16429.7 -11531.6    318.3   7291.4  27417.7 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.528e+05  1.462e+03   104.5   <2e-16 ***
m$residuals 4.960e-16  2.176e-01     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 12150 on 67 degrees of freedom
Multiple R-squared: 3.427e-31,	Adjusted R-squared: -0.01493 
F-statistic: 2.296e-29 on 1 and 67 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/wessaorg/rcomp/tmp/5ufpm1321379289.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 
-5619.8 -1915.1  -362.2  2105.3  6329.7 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 111.88995  345.30512   0.324    0.747    
Residuals     0.87841    0.05164  17.011   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2847 on 66 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8143,	Adjusted R-squared: 0.8115 
F-statistic: 289.4 on 1 and 66 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6cni11321379289.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7w9rd1321379289.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/89o841321379289.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/91rvo1321379289.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/10zdab1321379289.tab") 
> 
> try(system("convert tmp/1vdjq1321379289.ps tmp/1vdjq1321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/2m7il1321379289.ps tmp/2m7il1321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c6r61321379289.ps tmp/3c6r61321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mv861321379289.ps tmp/4mv861321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ufpm1321379289.ps tmp/5ufpm1321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cni11321379289.ps tmp/6cni11321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/7w9rd1321379289.ps tmp/7w9rd1321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/89o841321379289.ps tmp/89o841321379289.png",intern=TRUE))
character(0)
> try(system("convert tmp/91rvo1321379289.ps tmp/91rvo1321379289.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.523   0.415   3.141