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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> y <- c(12,11,14,12,21,12,22,11,10,13,10,8,15,14,10,14,14,11,10,13,7,14,12,14,11,9,11,15,14,13,9,15,10,11,13,8,20,12,10,10,9,14,8,14,11,13,9,11,15,11,10,14,18,14,11,12,13,9,10,15,20,12,12,14,13,11,17,12,13,14,13,15,13,10,11,19,13,17,13,9,11,10,9,12,12,13,13,12,15,22,13,15,13,15,10,11,16,11,11,10,10,16,12,11,16,19,11,16,15,24,14,15,11,15,12,10,14,13,9,15,15,14,11,8,11,11,8,10,11,13,11,20,10,15,12,14,23,14,16,11,12,10,14,12,12,11,12,13,11,19,12,17,9,12,19,18,15,14,11,9,18,16)
> x <- c(53,86,66,67,76,78,53,80,74,76,79,54,67,54,87,58,75,88,64,57,66,68,54,56,86,80,76,69,78,67,80,54,71,84,74,71,63,71,76,69,74,75,54,52,69,68,65,75,74,75,72,67,63,62,63,76,74,67,73,70,53,77,77,52,54,80,66,73,63,69,67,54,81,69,84,80,70,69,77,54,79,30,71,73,72,77,75,69,54,70,73,54,77,82,80,80,69,78,81,76,76,73,85,66,79,68,76,71,54,46,82,74,88,38,76,86,54,70,69,90,54,76,89,76,73,79,90,74,81,72,71,66,77,65,74,82,54,63,54,64,69,54,84,86,77,89,76,60,75,73,85,79,71,72,69,78,54,69,81,84,84,69)
> 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 
-6.3008 -1.6625 -0.4367  0.9346  9.0812 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 18.64034    1.60540  11.611  < 2e-16 ***
x           -0.08090    0.02245  -3.604 0.000418 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.054 on 160 degrees of freedom
Multiple R-squared: 0.07508,	Adjusted R-squared: 0.0693 
F-statistic: 12.99 on 1 and 160 DF,  p-value: 0.0004183 

> postscript(file="/var/wessaorg/rcomp/tmp/19pua1321558229.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/2ogcd1321558229.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 
-1.912e-15 -4.599e-16 -4.106e-17  4.791e-16  1.555e-15 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  1.864e+01  3.302e-16  5.645e+16   <2e-16 ***
x           -8.090e-02  4.618e-18 -1.752e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 6.283e-16 on 160 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 3.07e+32 on 1 and 160 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3tmq81321558229.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-6.3008 -1.6625 -0.4367  0.9346  9.0812 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.105e-16  1.605e+00       0        1
x            2.245e-18  2.245e-02       0        1

Residual standard error: 3.054 on 160 degrees of freedom
Multiple R-squared: 1.069e-34,	Adjusted R-squared: -0.00625 
F-statistic: 1.71e-32 on 1 and 160 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/420421321558229.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-1.5606 -0.5696 -0.1448  0.3810  3.2935 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.292e+01  6.837e-02     189   <2e-16 ***
m$residuals -3.923e-17  2.252e-02       0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.8702 on 160 degrees of freedom
Multiple R-squared: 1.042e-29,	Adjusted R-squared: -0.00625 
F-statistic: 1.667e-27 on 1 and 160 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/58hp21321558229.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 
-6.3432 -1.6787 -0.4392  0.9480  9.0372 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.01533    0.24085   0.064    0.949
Residuals    0.03938    0.07933   0.496    0.620

Residual standard error: 3.056 on 159 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.001547,	Adjusted R-squared: -0.004732 
F-statistic: 0.2464 on 1 and 159 DF,  p-value: 0.6203 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6otrw1321558230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7dyuc1321558230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8zt981321558230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9j3j71321558230.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/10kvld1321558230.tab") 
> 
> try(system("convert tmp/19pua1321558229.ps tmp/19pua1321558229.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ogcd1321558229.ps tmp/2ogcd1321558229.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tmq81321558229.ps tmp/3tmq81321558229.png",intern=TRUE))
character(0)
> try(system("convert tmp/420421321558229.ps tmp/420421321558229.png",intern=TRUE))
character(0)
> try(system("convert tmp/58hp21321558229.ps tmp/58hp21321558229.png",intern=TRUE))
character(0)
> try(system("convert tmp/6otrw1321558230.ps tmp/6otrw1321558230.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dyuc1321558230.ps tmp/7dyuc1321558230.png",intern=TRUE))
character(0)
> try(system("convert tmp/8zt981321558230.ps tmp/8zt981321558230.png",intern=TRUE))
character(0)
> try(system("convert tmp/9j3j71321558230.ps tmp/9j3j71321558230.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.517   0.428   2.961