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(278,201,331,650,126,74,962,96,463,371,438,299,352,603,350,944,390,583,288,373,389,689,218,265,675,611,625,293,361,466,514,284,430,131,605,552,616,323,209,595,848,409,363,226,791,1203,310,381,915,525,267,216,460,253,390,585,398,619,561,358,690,696,607,489,296,238,366,541,492,284,414,299,392,411,299,518,542,240,260,339,394,735,497,232,437,548,201,721,405,584,351,356,310,625,465,320,301,419,518,744,334,475,284,206,425,346,490,547,169,291,329,335,135,395,185,252,563,146,517,181,657,277,173,289,276,275,476,215,853,460,668,287,252,520,822,191,970,405,309,396,177,890,366,716,442,290,596,436,0,85,0,0,0,0,389,443,0,0,74,259,69,187,0,295)
> 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 
-77461 -17069  -2305  16352  49059 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 17068.53    3675.03   4.644 7.02e-06 ***
x              99.57       8.04  12.384  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 22580 on 162 degrees of freedom
Multiple R-squared: 0.4863,	Adjusted R-squared: 0.4831 
F-statistic: 153.4 on 1 and 162 DF,  p-value: < 2.2e-16 

> postscript(file="/var/wessaorg/rcomp/tmp/12h751321112631.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/2nykj1321112631.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 
-7.967e-11 -1.696e-12  6.220e-13  2.697e-12  1.383e-11 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.707e+04  1.286e-12 1.327e+16   <2e-16 ***
x           9.957e+01  2.815e-15 3.538e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 7.905e-12 on 162 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.251e+33 on 1 and 162 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3btyu1321112631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
   Min     1Q Median     3Q    Max 
-77461 -17069  -2305  16352  49059 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  1.223e-12  3.675e+03       0        1
x           -3.280e-15  8.040e+00       0        1

Residual standard error: 22580 on 162 degrees of freedom
Multiple R-squared: 9.904e-33,	Adjusted R-squared: -0.006173 
F-statistic: 1.604e-30 on 1 and 162 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4mjvn1321112631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
   Min     1Q Median     3Q    Max 
-39930 -13394  -2889  12743  79855 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  5.700e+04  1.716e+03   33.22   <2e-16 ***
m$residuals -6.233e-17  7.644e-02    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 21970 on 162 degrees of freedom
Multiple R-squared: 7.446e-32,	Adjusted R-squared: -0.006173 
F-statistic: 1.206e-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/5ttyv1321112631.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 
-78817 -16204  -1139  16002  47602 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -310.08846 1739.34138  -0.178    0.859
Residuals      0.09846    0.07737   1.273    0.205

Residual standard error: 22210 on 161 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.009959,	Adjusted R-squared: 0.00381 
F-statistic:  1.62 on 1 and 161 DF,  p-value: 0.205 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/62ofg1321112631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7dzgz1321112631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8zih21321112631.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/90o7n1321112631.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/10ns7z1321112631.tab") 
> 
> try(system("convert tmp/12h751321112631.ps tmp/12h751321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nykj1321112631.ps tmp/2nykj1321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/3btyu1321112631.ps tmp/3btyu1321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mjvn1321112631.ps tmp/4mjvn1321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ttyv1321112631.ps tmp/5ttyv1321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/62ofg1321112631.ps tmp/62ofg1321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dzgz1321112631.ps tmp/7dzgz1321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/8zih21321112631.ps tmp/8zih21321112631.png",intern=TRUE))
character(0)
> try(system("convert tmp/90o7n1321112631.ps tmp/90o7n1321112631.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.644   0.373   3.037