R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(14,18,11,12,16,18,14,14,15,15,17,19,10,18,14,14,17,14,16,18,14,12,17,9,16,14,11,16,13,17,15,14,16,9,15,17,13,15,16,16,12,12,11,15,17,13,16,14,11,12,12,15,16,15,12,12,8,13,11,14,15,10,11,12,15,15,14,16,15,15,13,17,13,15,13,15,16,15,16,15,14,15,7,17,13,15,14,13,16,12,14,17,15,17,12,16,11,15,9,16,10,10,15,11,13,14,18,16,14,14,14,14,12,14,15,15,15,13,17,17,19,15,13,9,15,15,16,11,14,11,15,13,15,16,14,15,16,16,11,13,16,12,9,13,13,14,19,13,12,13)
> x <- c(25,25,19,18,18,22,29,26,25,23,23,23,24,30,19,24,32,30,29,17,25,26,26,25,23,21,19,35,19,20,21,21,24,23,19,17,24,15,25,27,29,27,18,25,22,26,23,16,27,25,14,19,20,16,18,22,21,22,22,32,23,31,18,23,26,24,19,14,20,22,24,25,21,28,24,20,21,23,13,24,21,21,17,14,29,25,16,25,25,21,23,22,19,24,26,25,20,22,14,20,32,21,22,28,25,17,21,23,27,22,19,20,17,24,21,21,23,24,19,22,26,17,17,19,15,17,27,19,21,25,19,22,18,20,15,20,29,19,29,24,23,22,23,22,29,26,26,21,18,10)
> 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 
-6.96311 -1.19916  0.04739  1.81658  4.91100 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 13.60640    1.01470  13.409   <2e-16 ***
x            0.02098    0.04477   0.469     0.64    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.358 on 148 degrees of freedom
Multiple R-squared: 0.001482,	Adjusted R-squared: -0.005265 
F-statistic: 0.2197 on 1 and 148 DF,  p-value: 0.64 

> postscript(file="/var/www/html/rcomp/tmp/1uvy31289745675.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/html/rcomp/tmp/2uvy31289745675.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 
-4.865e-15 -1.321e-15 -8.502e-16 -4.079e-16  1.241e-13 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.361e+01  4.417e-15 3.080e+15   <2e-16 ***
x           2.098e-02  1.949e-16 1.077e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.026e-14 on 148 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.159e+28 on 1 and 148 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/34mxo1289745675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-6.96311 -1.19916  0.04739  1.81658  4.91100 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept)  1.707e-15  1.015e+00  1.68e-15        1
x           -7.588e-17  4.477e-02 -1.69e-15        1

Residual standard error: 2.358 on 148 degrees of freedom
Multiple R-squared: 3.345e-32,	Adjusted R-squared: -0.006757 
F-statistic: 4.951e-30 on 1 and 148 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4fdfr1289745675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-0.257106 -0.068263 -0.005316  0.057632  0.267457 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)    
(Intercept)  1.407e+01  7.418e-03      1897   <2e-16 ***
m$residuals -1.001e-16  3.167e-03 -3.16e-14        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.09085 on 148 degrees of freedom
Multiple R-squared: 5.957e-27,	Adjusted R-squared: -0.006757 
F-statistic: 8.817e-25 on 1 and 148 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/html/rcomp/tmp/5fdfr1289745675.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 
-6.9263 -1.2713  0.1327  1.7782  5.0256 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.001097   0.193684   0.006    0.995
Residuals   -0.039728   0.082446  -0.482    0.631

Residual standard error: 2.364 on 147 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.001577,	Adjusted R-squared: -0.005215 
F-statistic: 0.2322 on 1 and 147 DF,  p-value: 0.6306 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6d8li1289745675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7d8li1289745675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/86z2l1289745675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/96z2l1289745675.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/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/html/rcomp/tmp/10x6b61289745675.tab") 
> 
> try(system("convert tmp/1uvy31289745675.ps tmp/1uvy31289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/2uvy31289745675.ps tmp/2uvy31289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/34mxo1289745675.ps tmp/34mxo1289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fdfr1289745675.ps tmp/4fdfr1289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fdfr1289745675.ps tmp/5fdfr1289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/6d8li1289745675.ps tmp/6d8li1289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d8li1289745675.ps tmp/7d8li1289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/86z2l1289745675.ps tmp/86z2l1289745675.png",intern=TRUE))
character(0)
> try(system("convert tmp/96z2l1289745675.ps tmp/96z2l1289745675.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.882   1.400   2.347