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(93809,75589,61071,64672,39014,32213,131696,6853,43253,57555,85473,44501,42453,67285,57056,94982,89324,60461,64491,60717,83022,91708,28378,59360,54436,70629,95409,68631,42319,91440,100462,41411,94894,16617,114686,64881,106679,54866,45988,82618,79199,46657,71070,29970,42948,61186,47824,62913,101444,61145,58388,15049,81451,25109,44688,77378,80180,96279,115202,31648,119420,121683,46568,57903,71075,63394,58118,62099,63739,35768,53318,22330,57871,52090,50767,68496,101760,58441,38972,43530,38996,98432,49867,56434,55792,25155,43461,65474,82234,49606,47992,63723,39066,54501,69924,58204,80248,106887,82830,125642,62525,93166,30028,19630,56584,63525,68879,80800,56474,25551,77587,60521,5841,54108,24587,23872,116211,6622,83478,13155,87473,43580,10439,33067,13983,52276,81079,63507,106262,92878,120184,63110,29996,55746,105611,6783,69866,39663,93382,42310,1472,83141,70434,10901,66220,25867,71760,94809,0,7953,0,0,0,0,63404,89657,0,0,4245,21509,7670,10641,0,31359)
> x <- c(78973,46146,46492,60656,21898,36555,74680,22807,61282,37981,41553,45081,38557,51641,30658,52924,79256,53462,68950,53639,67819,48333,28001,51665,39019,46221,65792,39858,19574,41829,78688,36781,44314,24874,56911,37048,48426,33388,26998,46502,41507,40001,33144,29501,43059,43249,29272,49821,98341,44372,42448,5950,64839,32551,30767,62046,71930,67328,67253,35373,85544,88087,30621,50580,49670,25456,69245,43787,53638,35683,38008,18801,44324,51408,53880,55708,63858,183643,35660,41664,29883,62047,33321,46553,56622,15430,49379,58215,38253,77786,21331,55292,30105,37651,59370,46216,73122,93927,55935,93308,74344,78094,25625,43750,28995,47336,57582,60875,165877,32984,61638,36367,1168,40530,21427,15024,39088,855,80455,14116,43915,76705,40112,41821,8773,52045,51491,53470,53211,63091,131634,41745,23656,51442,54574,35708,66627,39585,50029,25266,34860,62759,62307,37238,42452,59820,75075,97567,0,6023,0,0,0,0,42420,31116,0,0,1644,6179,3926,23238,0,38818)
> 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 
-105379  -13489     725   11369   64494 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 2.140e+04  3.615e+03    5.92 1.86e-08 ***
x           7.755e-01  6.791e-02   11.42  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 23450 on 162 degrees of freedom
Multiple R-squared: 0.446,	Adjusted R-squared: 0.4425 
F-statistic: 130.4 on 1 and 162 DF,  p-value: < 2.2e-16 

> postscript(file="/var/wessaorg/rcomp/tmp/1z9yo1321113470.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/2eh301321113470.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 
-4.739e-11 -2.359e-12  4.030e-13  2.491e-12  1.282e-11 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 2.140e+04  8.288e-13 2.583e+16   <2e-16 ***
x           7.755e-01  1.557e-17 4.981e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.376e-12 on 162 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.481e+33 on 1 and 162 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3xdvi1321113470.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-105379  -13489     725   11369   64494 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.883e-13  3.615e+03       0        1
x            4.429e-18  6.791e-02       0        1

Residual standard error: 23450 on 162 degrees of freedom
Multiple R-squared: 3.979e-35,	Adjusted R-squared: -0.006173 
F-statistic: 6.446e-33 on 1 and 162 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4k8sm1321113470.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
   Min     1Q Median     3Q    Max 
-35595 -11532  -1652   9775 106821 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 5.700e+04  1.643e+03   34.69   <2e-16 ***
m$residuals 2.882e-17  7.049e-02    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 21040 on 162 degrees of freedom
Multiple R-squared: 1.986e-31,	Adjusted R-squared: -0.006173 
F-statistic: 3.217e-29 on 1 and 162 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/55lf71321113470.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 
-104737  -13443    1021   11196   64389 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  -66.16550 1841.01797  -0.036    0.971
Residuals     -0.01867    0.07892  -0.237    0.813

Residual standard error: 23500 on 161 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.0003474,	Adjusted R-squared: -0.005862 
F-statistic: 0.05596 on 1 and 161 DF,  p-value: 0.8133 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6x9cn1321113470.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7nvck1321113470.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8bsja1321113470.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/91izf1321113470.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/10z2fx1321113470.tab") 
> 
> try(system("convert tmp/1z9yo1321113470.ps tmp/1z9yo1321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/2eh301321113470.ps tmp/2eh301321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xdvi1321113470.ps tmp/3xdvi1321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/4k8sm1321113470.ps tmp/4k8sm1321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/55lf71321113470.ps tmp/55lf71321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/6x9cn1321113470.ps tmp/6x9cn1321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nvck1321113470.ps tmp/7nvck1321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bsja1321113470.ps tmp/8bsja1321113470.png",intern=TRUE))
character(0)
> try(system("convert tmp/91izf1321113470.ps tmp/91izf1321113470.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.529   0.422   3.004