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(76035,74427,73354,73081,75309,75463,75910,76151,76882,78632,80137,82490,79896,81303,79344,81355,82328,79669,77249,75101,72520,72438,72653,71429,69189,66451,63354,61379,61880,62274,62429,63905,63917,64295,61930,60440,59353,58695,60569,60386,60938,61795,63304,64270,63492,61333,59341,58412,58725,59277,58562,57858,58790,58243,57044,57339,59429,60575,61950,61712)
> x <- c(89924,31795,27922,59954,52150,39964,34604,51106,52593,68794,47124,32315,42248,36088,52744,72586,92334,80761,71078,63713,57122,55243,62143,62708,62474,64250,71866,69886,58724,55298,52594,54854,54694,49298,44659,43657,47002,47042,48959,49750,54048,60067,68929,74617,75940,72762,75621,73008,74196,78878,83812,91624,89388,110410,113857,112060,117236,132810,137699,146409)
> 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 
-11349  -6615  -1984   4987  18038 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  7.602e+04  2.751e+03  27.634  < 2e-16 ***
x           -1.270e-01  3.801e-02  -3.343  0.00146 ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 7623 on 58 degrees of freedom
Multiple R-squared: 0.1615,	Adjusted R-squared: 0.1471 
F-statistic: 11.17 on 1 and 58 DF,  p-value: 0.001458 

> postscript(file="/var/wessaorg/rcomp/tmp/1b0ys1321388749.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/26tx41321388749.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 
-3.813e-11 -2.579e-12  6.110e-13  3.525e-12  8.593e-12 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  7.602e+04  2.266e-12  3.354e+16   <2e-16 ***
x           -1.270e-01  3.131e-17 -4.057e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 6.28e-12 on 58 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.646e+31 on 1 and 58 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/30h3q1321388749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
   Min     1Q Median     3Q    Max 
-11349  -6615  -1984   4987  18038 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  4.865e-13  2.751e+03       0        1
x           -3.007e-18  3.801e-02       0        1

Residual standard error: 7623 on 58 degrees of freedom
Multiple R-squared: 1.908e-33,	Adjusted R-squared: -0.01724 
F-statistic: 1.107e-31 on 1 and 58 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4xobe1321388749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
   Min     1Q Median     3Q    Max 
-10014  -1030    671   2137   5040 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  6.743e+04  4.319e+02   156.1   <2e-16 ***
m$residuals -7.662e-17  5.763e-02     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3346 on 58 degrees of freedom
Multiple R-squared: 2.087e-29,	Adjusted R-squared: -0.01724 
F-statistic: 1.211e-27 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/wessaorg/rcomp/tmp/524m11321388749.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 
-8147.0 -1243.0  -206.7  1443.7  5288.8 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) -125.71418  295.92645  -0.425    0.673    
Residuals      0.93703    0.03926  23.867   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2273 on 57 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.909,	Adjusted R-squared: 0.9074 
F-statistic: 569.6 on 1 and 57 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6y6d21321388749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/76slp1321388749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8q4m21321388749.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/94lub1321388749.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/10frfg1321388749.tab") 
> 
> try(system("convert tmp/1b0ys1321388749.ps tmp/1b0ys1321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/26tx41321388749.ps tmp/26tx41321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/30h3q1321388749.ps tmp/30h3q1321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xobe1321388749.ps tmp/4xobe1321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/524m11321388749.ps tmp/524m11321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/6y6d21321388749.ps tmp/6y6d21321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/76slp1321388749.ps tmp/76slp1321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/8q4m21321388749.ps tmp/8q4m21321388749.png",intern=TRUE))
character(0)
> try(system("convert tmp/94lub1321388749.ps tmp/94lub1321388749.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.428   0.431   2.879