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(41,39,50,40,43,38,44,35,39,35,29,49,50,59,63,32,39,47,53,60,57,52,70,90,74,62,55,84,94,70,108,139,120,97,126,149,158,124,140,109,114,77,120,133,110,92,97,78,99,107,112,90,98,125,155,190,236,189,174,178,136,161,171,149,184,155,276,224,213,279,268,287,238,213,257,293,212,246,353,339,308,247,257,322,298,273,312,249,286,279,309,401,309,328,353,354,327,324,285,243,241,287,355,460,364,487,452,391,500,451,375,372,302,316,398,394,431,431)
> x <- c(1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10,11,12,1,2,3,4,5,6,7,8,9,10)
> par1 = '0'
> 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 
-187.50 -116.87  -29.75  101.26  327.59 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  168.006     24.999   6.721 7.12e-10 ***
x              4.409      3.439   1.282    0.202    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 127.7 on 116 degrees of freedom
Multiple R-squared: 0.01397,	Adjusted R-squared: 0.005468 
F-statistic: 1.643 on 1 and 116 DF,  p-value: 0.2024 

> postscript(file="/var/wessaorg/rcomp/tmp/1jugj1322054499.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/2r84w1322054499.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 
-3.310e-14 -1.561e-14 -2.872e-15  7.853e-15  2.673e-13 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.680e+02  5.884e-15 2.856e+16   <2e-16 ***
x           4.409e+00  8.094e-16 5.447e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.005e-14 on 116 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.967e+31 on 1 and 116 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3bozh1322054499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-187.50 -116.87  -29.75  101.26  327.59 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  5.508e-15  2.500e+01       0        1
x           -8.131e-16  3.439e+00       0        1

Residual standard error: 127.7 on 116 degrees of freedom
Multiple R-squared: 1.466e-33,	Adjusted R-squared: -0.008621 
F-statistic: 1.7e-31 on 1 and 116 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4og3j1322054499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-23.873 -13.954  -1.831  11.395  24.621 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.963e+02  1.399e+00   140.3   <2e-16 ***
m$residuals 1.925e-18  1.105e-02     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 15.2 on 116 degrees of freedom
Multiple R-squared: 1.929e-30,	Adjusted R-squared: -0.008621 
F-statistic: 2.238e-28 on 1 and 116 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/5ff9z1322054499.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 
-90.47 -26.03  -4.43  23.05 163.10 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.90067    3.95679   0.733    0.465    
Residuals    0.95000    0.03152  30.138   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 42.79 on 115 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8876,	Adjusted R-squared: 0.8866 
F-statistic: 908.3 on 1 and 115 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6c8wy1322054499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7d6g31322054499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8sxqc1322054499.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9s6vj1322054499.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/10e0fq1322054499.tab") 
> 
> try(system("convert tmp/1jugj1322054499.ps tmp/1jugj1322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/2r84w1322054499.ps tmp/2r84w1322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bozh1322054499.ps tmp/3bozh1322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/4og3j1322054499.ps tmp/4og3j1322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ff9z1322054499.ps tmp/5ff9z1322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/6c8wy1322054499.ps tmp/6c8wy1322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d6g31322054499.ps tmp/7d6g31322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/8sxqc1322054499.ps tmp/8sxqc1322054499.png",intern=TRUE))
character(0)
> try(system("convert tmp/9s6vj1322054499.ps tmp/9s6vj1322054499.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.718   0.567   3.374