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(31.293,30.236,30.160,32.436,30.695,27.525,26.434,25.739,25.204,24.977,24.320,22.680,22.052,21.467,21.383,21.777,21.928,21.814,22.937,23.595,20.830,19.650,19.195,19.644,18.483,18.079,19.178,18.391,18.441,18.584,20.108,20.148,19.394,17.745,17.696,17.032,16.438,15.683,15.594,15.713,15.937,16.171,15.928,16.348,15.579,15.305,15.648,14.954,15.137,15.839)
> x <- c(4797.4,4634.8,4424.2,4973.2,4616.7,4466.2,4758.4,3710.2,4189.8,4283.4,3984.8,4194.9,3942,3502.1,3531.6,3560.3,3477.3,3475.9,3954.1,3650.6,4283.1,4384,4460.3,5227.3,5894.8,4958.9,5384.9,5357.5,5027,5526.4,4744.1,4037.6,5363.5,4254.9,5126,5174.5,4329.7,4264.7,4711.9,4505.4,4608.3,4225.6,4623.4,4060.1,4570.6,3940.1,4610.6,4486.9,4029,3934.7)
> 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 
-5.8067 -4.4956 -0.7666  1.9180 12.2038 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept) 23.9798128  5.3275981   4.501 4.31e-05 ***
x           -0.0007536  0.0011888  -0.634    0.529    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4.822 on 48 degrees of freedom
Multiple R-squared: 0.008302,	Adjusted R-squared: -0.01236 
F-statistic: 0.4018 on 1 and 48 DF,  p-value: 0.5292 

> postscript(file="/var/www/rcomp/tmp/1cbpk1289926157.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/2cbpk1289926157.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 
-1.063e-14 -6.344e-16  1.067e-16  1.050e-15  2.141e-15 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  2.398e+01  2.081e-15  1.153e+16   <2e-16 ***
x           -7.536e-04  4.643e-19 -1.623e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.883e-15 on 48 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.635e+30 on 1 and 48 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3nlon1289926157.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-5.8067 -4.4956 -0.7666  1.9180 12.2038 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -1.778e-15  5.328e+00 -3.34e-16        1
x            3.988e-19  1.189e-03  3.35e-16        1

Residual standard error: 4.822 on 48 degrees of freedom
Multiple R-squared: 3.495e-33,	Adjusted R-squared: -0.02083 
F-statistic: 1.678e-31 on 1 and 48 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/4gu5q1289926157.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-1.092758 -0.233718  0.001827  0.311616  0.730030 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  2.063e+01  6.239e-02     330.7   <2e-16 ***
m$residuals -5.050e-17  1.321e-02 -3.82e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.4412 on 48 degrees of freedom
Multiple R-squared: 1.351e-30,	Adjusted R-squared: -0.02083 
F-statistic: 6.485e-29 on 1 and 48 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/5jv7n1289926158.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 
-2.26887 -0.53675 -0.04386  0.51296  3.65801 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.32147    0.14511  -2.215   0.0316 *  
Residuals    0.93201    0.03078  30.282   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.016 on 47 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.9512,	Adjusted R-squared: 0.9502 
F-statistic:   917 on 1 and 47 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/6jv7n1289926158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/7cm781289926158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/8cm781289926158.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/9cm781289926158.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/10154k1289926158.tab") 
> 
> try(system("convert tmp/1cbpk1289926157.ps tmp/1cbpk1289926157.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cbpk1289926157.ps tmp/2cbpk1289926157.png",intern=TRUE))
character(0)
> try(system("convert tmp/3nlon1289926157.ps tmp/3nlon1289926157.png",intern=TRUE))
character(0)
> try(system("convert tmp/4gu5q1289926157.ps tmp/4gu5q1289926157.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jv7n1289926158.ps tmp/5jv7n1289926158.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jv7n1289926158.ps tmp/6jv7n1289926158.png",intern=TRUE))
character(0)
> try(system("convert tmp/7cm781289926158.ps tmp/7cm781289926158.png",intern=TRUE))
character(0)
> try(system("convert tmp/8cm781289926158.ps tmp/8cm781289926158.png",intern=TRUE))
character(0)
> try(system("convert tmp/9cm781289926158.ps tmp/9cm781289926158.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.830   1.670   4.468