R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> y <- c(0.3,2.1,2.5,2.3,2.4,3,1.7,3.5,4,3.7,3.7,3,2.7,2.5,2.2,2.9,3.1,3,2.8,2.5,1.9,1.9,1.8,2,2.6,2.5,2.5,1.6,1.4,0.8,1.1,1.3,1.2,1.3,1.1,1.3,1.2,1.6,1.7,1.5,0.9,1.5,1.4,1.6,1.7,1.4,1.8,1.7,1.4,1.2,1,1.7,2.4,2,2.1,2,1.8,2.7,2.3,1.9,2,2.3,2.8,2.4,2.3,2.7,2.7,2.9,3,2.2,2.3,2.8,2.8,2.8,2.2,2.6,2.8,2.5,2.4,2.3,1.9,1.7,2,2.1,1.7,1.8,1.8,1.8,1.3,1.3,1.3,1.2,1.4,2.2,2.9,3.1,3.5,3.6,4.4,4.1,5.1,5.8,5.9,5.4,5.5,4.8,3.2,2.7,2.1,1.9,0.6,0.7,-0.2,-1,-1.7,-0.7,-1,-0.9,0,0.3,0.8,0.8,1.9,2.1,2.5,2.7,2.4,2.4,2.9,3.1,3)
> x <- c(493,481,462,457,442,439,488,521,501,485,464,460,467,460,448,443,436,431,484,510,513,503,471,471,476,475,470,461,455,456,517,525,523,519,509,512,519,517,510,509,501,507,569,580,578,565,547,555,562,561,555,544,537,543,594,611,613,611,594,595,591,589,584,573,567,569,621,629,628,612,595,597,593,590,580,574,573,573,620,626,620,588,566,557,561,549,532,526,511,499,555,565,542,527,510,514,517,508,493,490,469,478,528,534,518,506,502,516,528,533,536,537,524,536,587,597,581,564,558,575,580,575,563,552,537,545,601,604,586,564,549)
> 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 
-3.5616 -0.6958  0.0264  0.6283  3.7236 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  4.994073   1.161247   4.301 3.33e-05 ***
x           -0.005336   0.002158  -2.473   0.0147 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.225 on 129 degrees of freedom
Multiple R-squared: 0.04525,	Adjusted R-squared: 0.03784 
F-statistic: 6.113 on 1 and 129 DF,  p-value: 0.01472 

> postscript(file="/var/www/rcomp/tmp/11bqe1293481324.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/www/rcomp/tmp/21bqe1293481324.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 
-3.430e-16 -7.562e-17 -3.152e-17  1.553e-16  3.628e-16 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  4.994e+00  1.469e-16  3.399e+16   <2e-16 ***
x           -5.336e-03  2.731e-19 -1.954e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.55e-16 on 129 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 3.818e+32 on 1 and 129 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3c37z1293481324.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-3.5616 -0.6958  0.0264  0.6283  3.7236 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  1.723e-17  1.161e+00       0        1
x           -4.608e-21  2.158e-03       0        1

Residual standard error: 1.225 on 129 degrees of freedom
Multiple R-squared:     0,	Adjusted R-squared: -0.007752 
F-statistic:     0 on 1 and 129 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/4mu721293481324.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
     Min       1Q   Median       3Q      Max 
-0.49768 -0.20684 -0.00139  0.17739  0.55894 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.135e+00  2.330e-02   91.62   <2e-16 ***
m$residuals -1.642e-17  1.917e-02    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.2667 on 129 degrees of freedom
Multiple R-squared: 5.373e-31,	Adjusted R-squared: -0.007752 
F-statistic: 6.931e-29 on 1 and 129 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/rcomp/tmp/5fl651293481324.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 
-1.39659 -0.29539 -0.01795  0.27853  1.88572 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.02236    0.04435   0.504    0.615    
Residuals    0.90140    0.03642  24.748   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 0.5057 on 128 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.8271,	Adjusted R-squared: 0.8258 
F-statistic: 612.5 on 1 and 128 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/6fl651293481324.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/78un81293481324.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/88un81293481324.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/9jm4t1293481324.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/10fd2k1293481324.tab") 
> 
> try(system("convert tmp/11bqe1293481324.ps tmp/11bqe1293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/21bqe1293481324.ps tmp/21bqe1293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c37z1293481324.ps tmp/3c37z1293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mu721293481324.ps tmp/4mu721293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fl651293481324.ps tmp/5fl651293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/6fl651293481324.ps tmp/6fl651293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/78un81293481324.ps tmp/78un81293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/88un81293481324.ps tmp/88un81293481324.png",intern=TRUE))
character(0)
> try(system("convert tmp/9jm4t1293481324.ps tmp/9jm4t1293481324.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   2.40    1.45    3.84