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(14,18,11,12,16,18,14,14,15,15,17,19,10,16,18,14,14,17,14,16,18,11,14,12,17,9,16,14,15,11,16,13,17,15,14,16,9,15,17,13,15,16,16,12,12,11,15,15,17,13,16,14,11,12,12,15,16,15,12,12,8,13,11,14,15,10,11,12,15,15,14,16,15,15,13,12,17,13,15,13,15,16,15,16,15,14,15,14,13,7,17,13,15,14,13,16,12,14,17,15,17,12,16,11,15,9,16,15,10,10,15,11,13,14,18,16,14,14,14,14,12,14,15,15,15,13,17,17,19,15,13,9,15,15,15,16,11,14,11,15,13,15,16,14,15,16,16,11,12,9,16,13,16,12,9,13,13,14,19,13,12,13)
> 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 
-8.2971 -1.1206  0.5264  1.2324  4.7029 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 12.47283    1.06745  11.685   <2e-16 ***
x            0.17652    0.07502   2.353   0.0198 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.225 on 160 degrees of freedom
Multiple R-squared: 0.03345,	Adjusted R-squared: 0.02741 
F-statistic: 5.537 on 1 and 160 DF,  p-value: 0.01984 

> postscript(file="/var/wessaorg/rcomp/tmp/1u4dh1356015348.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/2fi6i1356015348.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 
-1.870e-15 -4.319e-16  1.303e-16  5.124e-16  8.158e-16 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.247e+01  2.847e-16 4.381e+16   <2e-16 ***
x           1.765e-01  2.001e-17 8.821e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.935e-16 on 160 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 7.782e+31 on 1 and 160 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3pjyj1356015348.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-8.2971 -1.1206  0.5264  1.2324  4.7029 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  6.033e-17  1.067e+00       0        1
x           -4.692e-18  7.502e-02       0        1

Residual standard error: 2.225 on 160 degrees of freedom
Multiple R-squared: 3.5e-35,	Adjusted R-squared: -0.00625 
F-statistic: 5.6e-33 on 1 and 160 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4et8o1356015348.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-1.24216 -0.18306 -0.00654  0.34650  0.87605 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.495e+01  3.252e-02   459.7   <2e-16 ***
m$residuals 8.725e-19  1.471e-02     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.4139 on 160 degrees of freedom
Multiple R-squared: 7.781e-29,	Adjusted R-squared: -0.00625 
F-statistic: 1.245e-26 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/53lx71356015348.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 
-8.2257 -1.1495  0.4246  1.2773  4.8052 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept)  0.01112    0.17482   0.064    0.949
Residuals    0.08743    0.07897   1.107    0.270

Residual standard error: 2.218 on 159 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.007651,	Adjusted R-squared: 0.00141 
F-statistic: 1.226 on 1 and 159 DF,  p-value: 0.2699 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6m77i1356015348.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7uudf1356015348.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8gzex1356015348.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9boxq1356015348.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/10uayy1356015348.tab") 
> 
> try(system("convert tmp/1u4dh1356015348.ps tmp/1u4dh1356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/2fi6i1356015348.ps tmp/2fi6i1356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pjyj1356015348.ps tmp/3pjyj1356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/4et8o1356015348.ps tmp/4et8o1356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/53lx71356015348.ps tmp/53lx71356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/6m77i1356015348.ps tmp/6m77i1356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/7uudf1356015348.ps tmp/7uudf1356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/8gzex1356015348.ps tmp/8gzex1356015348.png",intern=TRUE))
character(0)
> try(system("convert tmp/9boxq1356015348.ps tmp/9boxq1356015348.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  4.984   0.819   5.813