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(59,68,79,96,119,112,91)
> x <- c(2000,2001,2002,2003,2004,2005,2006)
> 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:
      1       2       3       4       5       6       7 
 -6.143  -5.143  -2.143   6.857  21.857   6.857 -22.143 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)  
(Intercept) -15934.857   5692.736  -2.799   0.0380 *
x                8.000      2.842   2.815   0.0373 *
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 15.04 on 5 degrees of freedom
Multiple R-squared: 0.6131,	Adjusted R-squared: 0.5357 
F-statistic: 7.923 on 1 and 5 DF,  p-value: 0.03734 

> postscript(file="/var/wessaorg/rcomp/tmp/18b1o1321370244.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/279qu1321370244.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:
         1          2          3          4          5          6          7 
-8.400e-16 -5.809e-16  3.617e-15 -3.377e-15  3.976e-15 -4.343e-15  1.548e-15 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept) -1.593e+04  1.339e-12 -1.190e+16   <2e-16 ***
x            8.000e+00  6.687e-16  1.196e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.538e-15 on 5 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.431e+32 on 1 and 5 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3ifr71321370244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
      1       2       3       4       5       6       7 
 -6.143  -5.143  -2.143   6.857  21.857   6.857 -22.143 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -4.204e-13  5.693e+03       0        1
x            2.094e-16  2.842e+00       0        1

Residual standard error: 15.04 on 5 degrees of freedom
Multiple R-squared: 5.979e-34,	Adjusted R-squared:  -0.2 
F-statistic: 2.99e-33 on 1 and 5 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/49qme1321370244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
         1          2          3          4          5          6          7 
-2.400e+01 -1.600e+01 -8.000e+00 -2.748e-13  8.000e+00  1.600e+01  2.400e+01 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 8.914e+01  7.155e+00   12.46 5.91e-05 ***
m$residuals 1.994e-17  5.630e-01    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 18.93 on 5 degrees of freedom
Multiple R-squared:     0,	Adjusted R-squared:  -0.2 
F-statistic:     0 on 1 and 5 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/56yh91321370244.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:
       2        3        4        5        6        7 
 -3.4715  -0.7456   7.4322  19.9654   0.8542 -24.0346 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.01231    7.06411   0.002    0.999
Residuals    0.27408    0.68369   0.401    0.709

Residual standard error: 16.16 on 4 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.03863,	Adjusted R-squared: -0.2017 
F-statistic: 0.1607 on 1 and 4 DF,  p-value: 0.709 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6s6f61321370244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/71kps1321370244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/84dyd1321370244.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9o01v1321370244.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/10asqt1321370244.tab") 
> 
> try(system("convert tmp/18b1o1321370244.ps tmp/18b1o1321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/279qu1321370244.ps tmp/279qu1321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ifr71321370244.ps tmp/3ifr71321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/49qme1321370244.ps tmp/49qme1321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/56yh91321370244.ps tmp/56yh91321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/6s6f61321370244.ps tmp/6s6f61321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/71kps1321370244.ps tmp/71kps1321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/84dyd1321370244.ps tmp/84dyd1321370244.png",intern=TRUE))
character(0)
> try(system("convert tmp/9o01v1321370244.ps tmp/9o01v1321370244.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.415   0.434   2.888