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(36.805,36.75,36.645,36.855,36.535,36.655,36.40,36.50,36.425,37.005,36.75,37.06,37.00,36.955,36.905,36.80,36.61,36.40,35.87,35.215,35.65,35.79,35.72,36.305,35.80,36.135,36.395,36.435,36.755,36.85,36.90,37.16,37.48,37.775,37.90,38.01,37.68,38.06,37.83,37.605,38.02,38.065,38.21,38.00,38.335,38.51,38.30,38.345,38.185,38.60,38.965,38.36,38.54,38.425,38.625,39.025,38.91,39.24,39.66)
> x <- c(56.89,57.95,57.75,57.50,57.52,56.70,56.20,56.00,56.05,56.70,56.44,56.45,56.32,56.56,57.15,57.40,59.74,59.65,59.13,57.57,56.26,56.71,56.69,56.98,56.18,56.50,57.65,57.82,57.61,57.87,57.41,57.45,57.38,57.84,58.54,58.47,59.29,59.25,59.11,59.03,59.86,59.34,59.97,58.50,59.09,59.61,58.99,59.54,59.79,59.26,58.46,58.44,58.08,56.80,56.79,57.12,57.26,57.05,57.24)
> 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 
-2.0311 -0.5698 -0.0564  0.4238  2.5335 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)   
(Intercept)  16.3731     6.1743   2.652  0.01035 * 
x             0.3626     0.1068   3.395  0.00125 **
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.955 on 57 degrees of freedom
Multiple R-squared: 0.1682,	Adjusted R-squared: 0.1536 
F-statistic: 11.53 on 1 and 57 DF,  p-value: 0.001253 

> postscript(file="/var/wessaorg/rcomp/tmp/1o6qe1321312419.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/259oy1321312419.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 
-3.580e-15 -1.561e-15 -1.486e-16  1.603e-15  8.211e-15 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 1.637e+01  1.402e-14 1.168e+15   <2e-16 ***
x           3.626e-01  2.424e-16 1.496e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.168e-15 on 57 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.237e+30 on 1 and 57 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/39qml1321312419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-2.0311 -0.5698 -0.0564  0.4238  2.5335 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  4.147e-16  6.174e+00       0        1
x           -6.916e-18  1.068e-01       0        1

Residual standard error: 0.955 on 57 degrees of freedom
Multiple R-squared: 1.392e-33,	Adjusted R-squared: -0.01754 
F-statistic: 7.935e-32 on 1 and 57 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4k2nj1321312419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.65692 -0.36868 -0.08769  0.43441  0.78247 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  3.733e+01  5.592e-02   667.7   <2e-16 ***
m$residuals -2.988e-16  5.957e-02     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.4295 on 57 degrees of freedom
Multiple R-squared: 1.2e-28,	Adjusted R-squared: -0.01754 
F-statistic: 6.842e-27 on 1 and 57 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/5c4rw1321312419.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 
-1.08513 -0.20675 -0.05301  0.25808  0.86479 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.04708    0.04446   1.059    0.294    
Residuals    1.00094    0.05016  19.954   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.3382 on 56 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8767,	Adjusted R-squared: 0.8745 
F-statistic: 398.2 on 1 and 56 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6h5un1321312419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7psp41321312419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/81w1p1321312419.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/92r481321312419.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/100t6a1321312419.tab") 
> 
> try(system("convert tmp/1o6qe1321312419.ps tmp/1o6qe1321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/259oy1321312419.ps tmp/259oy1321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/39qml1321312419.ps tmp/39qml1321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/4k2nj1321312419.ps tmp/4k2nj1321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/5c4rw1321312419.ps tmp/5c4rw1321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/6h5un1321312419.ps tmp/6h5un1321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/7psp41321312419.ps tmp/7psp41321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/81w1p1321312419.ps tmp/81w1p1321312419.png",intern=TRUE))
character(0)
> try(system("convert tmp/92r481321312419.ps tmp/92r481321312419.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.490   0.447   3.000