R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> y <- c(13,16,19,15,14,13,19,15,14,15,16,16,16,16,17,15,15,20,18,16,16,16,19,16,17,17,16,15,16,14,15,12,14,16,14,7,10,14,16,16,16,14,20,14,14,11,14,15,16,14,16,14,12,16,9,14,16,16,15,16,12,16,16,14,16,17,18,18,12,16,10,14,18,18,16,17,16,16,13,16,16,20,16,15,15,16,14,16,16,15,12,17,16,15,13,16,16,16,16,14,16,16,20,15,16,13,17,16,16,12,16,16,17,13,12,18,14,14,13,16,13,16,13,16,15,16,15,17,15,12,16,10,16,12,14,15,13,15,11,12,8,16,15,17,16,10,18,13,16,13,10,15,16,16,14,10,17,13,15,16,12,13)
> x <- 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)
> par1 = '0'
> par1 <- '0'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), Linear Regression Graphical Model Validation (v1.0.7) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_linear_regression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> 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 
-8.7665 -1.1031  0.3994  1.2285  5.5552 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 17.09310    0.72870  23.457  < 2e-16 ***
x           -0.16583    0.05479  -3.027  0.00288 ** 
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.201 on 160 degrees of freedom
Multiple R-squared: 0.05415,	Adjusted R-squared: 0.04824 
F-statistic:  9.16 on 1 and 160 DF,  p-value: 0.002883 

> postscript(file="/var/fisher/rcomp/tmp/1oliy1355997419.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/fisher/rcomp/tmp/2me2k1355997419.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 
-1.367e-15 -4.820e-16 -3.559e-16  4.094e-16  8.685e-15 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  1.709e+01  2.791e-16  6.125e+16   <2e-16 ***
x           -1.658e-01  2.098e-17 -7.903e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 8.429e-16 on 160 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 6.247e+31 on 1 and 160 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/3dhqm1355997419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-8.7665 -1.1031  0.3994  1.2285  5.5552 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  3.575e-17  7.287e-01       0        1
x           -2.560e-18  5.479e-02       0        1

Residual standard error: 2.201 on 160 degrees of freedom
Multiple R-squared: 2.117e-33,	Adjusted R-squared: -0.00625 
F-statistic: 3.387e-31 on 1 and 160 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/40fsu1355997419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-1.8374 -0.1791  0.1525  0.3184  0.9817 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.495e+01  4.138e-02   361.3   <2e-16 ***
m$residuals -3.656e-17  1.892e-02     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.5267 on 160 degrees of freedom
Multiple R-squared: 2.844e-29,	Adjusted R-squared: -0.00625 
F-statistic: 4.55e-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/fisher/rcomp/tmp/5dcby1355997419.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 
-8.7074 -1.0433  0.3439  1.2631  5.7030 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.01238    0.17302   0.072    0.943
Residuals    0.07619    0.07895   0.965    0.336

Residual standard error: 2.195 on 159 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.005822,	Adjusted R-squared: -0.0004307 
F-statistic: 0.9311 on 1 and 159 DF,  p-value: 0.336 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/6r5wd1355997419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/7voi41355997419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/88u8r1355997419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/9w7af1355997419.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/10bzvw1355997419.tab") 
> 
> try(system("convert tmp/1oliy1355997419.ps tmp/1oliy1355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/2me2k1355997419.ps tmp/2me2k1355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dhqm1355997419.ps tmp/3dhqm1355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/40fsu1355997419.ps tmp/40fsu1355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/5dcby1355997419.ps tmp/5dcby1355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/6r5wd1355997419.ps tmp/6r5wd1355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/7voi41355997419.ps tmp/7voi41355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/88u8r1355997419.ps tmp/88u8r1355997419.png",intern=TRUE))
character(0)
> try(system("convert tmp/9w7af1355997419.ps tmp/9w7af1355997419.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.402   1.474   6.909