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(330,331.6,351.2,389.4,410.9,442.8,462.8,466.9,461.7,439.2,430.3,416.1,402.5,397.3,403.3,395.9,387.8,378.6,377.1,370.4,362,350.3,348.2,344.6,343.5,342.8,347.6,346.6,349.5,342.1,342,342.8,339.3,348.2,333.7,334.7,354,367.7,363.3,358.4,353.1,343.1,344.6,344.4,333.9,331.7,324.3,321.2,322.4,321.7,320.5,312.8,309.7,315.6,309.7,304.6,302.5,301.5,298.8,291.3,293.6,294.6,285.9,297.6,301.1,293.8,297.7,292.9,292.1,287.2,288.2,283.8,299.9,292.4,293.3,300.8,293.7,293.1,294.4,292.1,291.9,282.5,277.9,287.5,289.2,285.6,293.2,290.8,283.1,275,287.8,287.8,287.4,284,277.8,277.6,304.9,294,300.9,324,332.9,341.6,333.4,348.2,344.7,344.7,329.3,323.5,323.2,317.4,330.1,329.2,334.9,315.8,315.4,319.6,317.3,313.8,315.8,311.3)
> x <- c(94.45,113.44,157.33,147.38,171.89,171.95,132.71,126.02,121.18,115.45,110.48,117.85,117.63,124.65,109.59,111.27,99.78,98.21,99.2,97.97,89.55,87.91,93.34,94.42,93.2,90.29,91.46,89.98,88.35,88.41,82.44,79.89,75.69,75.66,84.5,96.73,87.48,82.39,83.48,79.31,78.16,72.77,72.45,68.46,67.62,68.76,70.07,68.55,65.3,58.96,59.17,62.37,66.28,55.62,55.23,55.85,56.75,50.89,53.88,52.95,55.08,53.61,58.78,61.85,55.91,53.32,46.41,44.57,50,50,53.36,46.23,50.45,49.07,45.85,48.45,49.96,46.53,50.51,47.58,48.05,46.84,47.67,49.16,55.54,55.82,58.22,56.19,57.77,63.19,54.76,55.74,62.54,61.39,69.6,79.23,80,93.68,107.63,100.18,97.3,90.45,80.64,80.58,75.82,85.59,89.35,89.42,104.73,95.32,89.27,90.44,86.97,79.98,81.22,87.35,83.64,82.22,94.4,102.18)
> 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 
-79.151 -13.784   1.209  13.582  77.833 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 228.04637    7.35497   31.01   <2e-16 ***
x             1.28586    0.08792   14.62   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 25.55 on 118 degrees of freedom
Multiple R-squared: 0.6445,	Adjusted R-squared: 0.6415 
F-statistic: 213.9 on 1 and 118 DF,  p-value: < 2.2e-16 

> postscript(file="/var/wessaorg/rcomp/tmp/1jof71321539876.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/2guq81321539876.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 
-3.032e-14 -1.222e-14 -3.423e-15  1.299e-14  6.665e-14 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 2.280e+02  4.762e-15 4.789e+16   <2e-16 ***
x           1.286e+00  5.692e-17 2.259e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.654e-14 on 118 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 5.103e+32 on 1 and 118 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/35cxd1321539876.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-79.151 -13.784   1.209  13.582  77.833 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -4.622e-16  7.355e+00       0        1
x            1.658e-17  8.792e-02       0        1

Residual standard error: 25.55 on 118 degrees of freedom
Multiple R-squared: 8.445e-33,	Adjusted R-squared: -0.008475 
F-statistic: 9.965e-31 on 1 and 118 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/40bq41321539876.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-44.707 -30.212   0.337  18.114 119.086 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 3.301e+02  3.140e+00   105.1   <2e-16 ***
m$residuals 1.315e-17  1.239e-01     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 34.4 on 118 degrees of freedom
Multiple R-squared: 5.207e-30,	Adjusted R-squared: -0.008475 
F-statistic: 6.144e-28 on 1 and 118 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/5kmvg1321539876.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 
-43.132  -6.555  -0.729   5.542  69.664 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.17878    1.28715  -0.139     0.89    
Residuals    0.84699    0.05137  16.487   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 14.04 on 117 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.6991,	Adjusted R-squared: 0.6965 
F-statistic: 271.8 on 1 and 117 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/63w2b1321539876.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7g4u51321539876.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8e87x1321539877.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9xm4d1321539877.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/10hvln1321539877.tab") 
> 
> try(system("convert tmp/1jof71321539876.ps tmp/1jof71321539876.png",intern=TRUE))
character(0)
> try(system("convert tmp/2guq81321539876.ps tmp/2guq81321539876.png",intern=TRUE))
character(0)
> try(system("convert tmp/35cxd1321539876.ps tmp/35cxd1321539876.png",intern=TRUE))
character(0)
> try(system("convert tmp/40bq41321539876.ps tmp/40bq41321539876.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kmvg1321539876.ps tmp/5kmvg1321539876.png",intern=TRUE))
character(0)
> try(system("convert tmp/63w2b1321539876.ps tmp/63w2b1321539876.png",intern=TRUE))
character(0)
> try(system("convert tmp/7g4u51321539876.ps tmp/7g4u51321539876.png",intern=TRUE))
character(0)
> try(system("convert tmp/8e87x1321539877.ps tmp/8e87x1321539877.png",intern=TRUE))
character(0)
> try(system("convert tmp/9xm4d1321539877.ps tmp/9xm4d1321539877.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.605   0.422   3.100