R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(17681.2,19858.9,16997.5,16969.9,18908.9,15692.1,15160,15806.8,16007.1,16059.1,16189.4,12522.5,14733.8,15686.3,13779.7,14423.8,15290.6,14308.3,13855.6,14384.5,15638.6,19711.6,20359.8,16141.4,20056.9,20605.5,19325.8,20547.7,19211.2,19009.5,18746.8,16471.5,18957.2,20515.2,18374.4,16192.9,18147.5,19301.4,18344.7,17183.6,19630,17167.2,17428.5,16016.5,18466.5,18406.6,18174.1,14851.9,16260.7,18329.6,18003.8,15903.8,19554.2,16554.2,16198.9)
> x <- c(17203.6,19542.1,17332.7,17962.5,18664.9,15878.6,16014.6,16867.9,16014,16793.9,16127.6,13557.7,14238.2,15465.9,13881,14346.9,15668.8,14521.1,15071.8,15816.8,17180.4,20432.3,21289.5,18203.6,20159.5,21053.2,19673.6,21473.3,20244.7,19049.6,20194.3,18021.9,19537.3,20286.6,17967.7,16409.9,17802.7,18509.9,18161.3,16721.3,19106.9,16772.1,17463.6,16162.3,17862.9,17664.9,17180.8,15672.7,15189.8,17699.4,17444.6,15930.7,19691.6,16698,16896.2)
> 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 
-1802.6  -533.8    56.1   593.2  1212.3 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 461.71691  876.96205   0.526    0.601    
x             0.96038    0.04989  19.249   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 721 on 53 degrees of freedom
Multiple R-squared: 0.8749,	Adjusted R-squared: 0.8725 
F-statistic: 370.5 on 1 and 53 DF,  p-value: < 2.2e-16 

> postscript(file="/var/www/rcomp/tmp/1ybax1289471712.ps",horizontal=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/www/rcomp/tmp/2ybax1289471712.ps",horizontal=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 
-3.094e-12 -4.938e-13 -6.660e-14  6.217e-13  2.104e-12 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 4.617e+02  1.181e-12 3.910e+14   <2e-16 ***
x           9.604e-01  6.719e-17 1.429e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 9.709e-13 on 53 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.043e+32 on 1 and 53 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3r29z1289471712.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-1802.6  -533.8    56.1   593.2  1212.3 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -6.605e-14  8.770e+02 -7.53e-17        1
x            5.855e-18  4.989e-02  1.17e-16        1

Residual standard error: 721 on 53 degrees of freedom
Multiple R-squared: 1.336e-33,	Adjusted R-squared: -0.01887 
F-statistic: 7.078e-32 on 1 and 53 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/4kbq31289471712.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-3756.1 -1396.8  -130.6  1333.5  3845.9 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 1.724e+04  2.570e+02    67.06   <2e-16 ***
m$residuals 1.686e-17  3.632e-01 4.64e-17        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1906 on 53 degrees of freedom
Multiple R-squared: 1.718e-30,	Adjusted R-squared: -0.01887 
F-statistic: 9.106e-29 on 1 and 53 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/www/rcomp/tmp/5dk851289471712.ps",horizontal=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 
-1568.49  -487.35    10.40   494.91  1490.34 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)   
(Intercept) -16.5185    90.0058  -0.184  0.85510   
Residuals     0.3972     0.1266   3.139  0.00280 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 661.4 on 52 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.1593,	Adjusted R-squared: 0.1431 
F-statistic: 9.851 on 1 and 52 DF,  p-value: 0.002796 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/6dk851289471712.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/7nbp81289471712.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/8nbp81289471712.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/9g3ot1289471712.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/10uv421289471712.tab") 
> 
> try(system("convert tmp/1ybax1289471712.ps tmp/1ybax1289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ybax1289471712.ps tmp/2ybax1289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/3r29z1289471712.ps tmp/3r29z1289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/4kbq31289471712.ps tmp/4kbq31289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/5dk851289471712.ps tmp/5dk851289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dk851289471712.ps tmp/6dk851289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nbp81289471712.ps tmp/7nbp81289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/8nbp81289471712.ps tmp/8nbp81289471712.png",intern=TRUE))
character(0)
> try(system("convert tmp/9g3ot1289471712.ps tmp/9g3ot1289471712.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   2.82    1.64    4.48