R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> y <- c(100.44,100.88,101.42,99.97,100.56,99.51,98.96,100.85,100.66,100.22,100.30,100.73,101.46,101.35,101.14,101.68,101.47,100.59,101.18,100.87,99.79,100.74,99.34,100.07,103.68,103.52,104.68,103.75,103.70,102.98,106.30,107.21,106.83,105.60,104.30,104.43,104.36,106.21,107.34,106.92,104.80,103.85,103.39,103.38,103.93,104.41,104.47,103.84,103.65,103.17,103.40,112.72,114.77,116.18,116.93,115.19,114.55)
> x <- c(1576.23,1546.37,1545.05,1552.34,1594.3,1605.78,1673.21,1612.94,1566.34,1530.17,1582.54,1702.16,1701.93,1811.15,1924.2,2034.25,2011.13,2013.04,2151.67,1902.09,1944.01,1916.67,1967.31,2119.88,2216.38,2522.83,2647.64,2631.23,2693.41,3021.76,2953.67,2796.8,2672.05,2251.23,2046.08,2420.04,2608.89,2660.47,2493.98,2541.7,2554.6,2699.61,2805.48,2956.66,3149.51,3372.5,3379.33,3517.54,3527.34,3281.06,3089.65,3222.76,3165.76,3232.43,3229.54,3071.74,2850.17)
> 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 
-5.6187 -1.6658 -0.2903  0.8602  9.0517 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 9.280e+01  1.764e+00  52.614  < 2e-16 ***
x           4.669e-03  7.111e-04   6.565 1.94e-08 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.335 on 55 degrees of freedom
Multiple R-squared: 0.4394,	Adjusted R-squared: 0.4292 
F-statistic:  43.1 on 1 and 55 DF,  p-value: 1.940e-08 

> postscript(file="/var/www/html/rcomp/tmp/1t12b1289599372.ps",horizontal=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/www/html/rcomp/tmp/2ms2e1289599372.ps",horizontal=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 
-2.488e-14 -1.465e-14 -7.378e-15 -2.067e-16  4.064e-13 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 9.280e+01  2.979e-14 3.115e+15   <2e-16 ***
x           4.669e-03  1.201e-17 3.887e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.632e-14 on 55 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.511e+29 on 1 and 55 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3fjjh1289599372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-5.6187 -1.6658 -0.2903  0.8602  9.0517 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -4.568e-16  1.764e+00 -2.59e-16        1
x            1.657e-19  7.111e-04  2.33e-16        1

Residual standard error: 3.335 on 55 degrees of freedom
Multiple R-squared: 2.513e-33,	Adjusted R-squared: -0.01818 
F-statistic: 1.382e-31 on 1 and 55 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4fjjh1289599372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-4.0667 -2.3303  0.4332  2.5794  5.2578 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 1.040e+02  3.910e-01      266   <2e-16 ***
m$residuals 1.437e-16  1.194e-01 1.20e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.952 on 55 degrees of freedom
Multiple R-squared: 3.413e-29,	Adjusted R-squared: -0.01818 
F-statistic: 1.877e-27 on 1 and 55 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/www/html/rcomp/tmp/5uw7r1289599372.ps",horizontal=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 
-2.5215 -1.0532 -0.3059  0.5928  8.2570 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.13362    0.22722   0.588    0.559    
Residuals    0.91951    0.07315  12.570   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.698 on 54 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.7453,	Adjusted R-squared: 0.7406 
F-statistic:   158 on 1 and 54 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/60kh51289599372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/70kh51289599372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8tth81289599372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9tth81289599372.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> qqnorm(x)
> qqline(x)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/www/html/rcomp/tmp/1073wh1289599372.tab") 
> 
> try(system("convert tmp/1t12b1289599372.ps tmp/1t12b1289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ms2e1289599372.ps tmp/2ms2e1289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fjjh1289599372.ps tmp/3fjjh1289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fjjh1289599372.ps tmp/4fjjh1289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/5uw7r1289599372.ps tmp/5uw7r1289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/60kh51289599372.ps tmp/60kh51289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/70kh51289599372.ps tmp/70kh51289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/8tth81289599372.ps tmp/8tth81289599372.png",intern=TRUE))
character(0)
> try(system("convert tmp/9tth81289599372.ps tmp/9tth81289599372.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.808   1.370  10.261