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(58.951,59.634,58.389,57.702,56.593,55.998,57.363,58.022,57.598,57.842,58.875,59.103,58.484,58.636,61.342,63.470,64.281,63.721,62.657,62.549,61.882,62.325,61.907,63.136,63.982,65.800,67.596,68.654,67.548,67.398,66.999,66.284,65.561,67.694,69.976,72.908,75.128,75.522,75.242,75.179,75.572,78.340,80.107,82.972,81.638,80.018,80.631,79.211,79.999,77.789,76.205,75.352,74.393,72.771,70.682,69.991,67.525,67.779,66.864,67.971,67.071,66.980,57.144,56.648,53.706,47.108,43.292,48.489,52.642,53.249,50.722,49.805,49.303,49.985,49.512,51.282,50.734,50.365,46.191,44.617,42.012,41.027,39.478,36.824,34.761,31.295,28.951,25.872,17.297,10.739,9.087,8.658,8.731,8.358,6.518,5.021,3.440,2.523,1.725,1.210,777,498,312,179,92,106)
> x <- c(61.712,62.084,61.406,60.724,58.904,58.722,59.704,60.674,59.813,60.568,61.401,61.427,61.080,61.999,63.888,66.284,67.309,66.685,65.404,65.045,63.867,64.156,62.224,63.193,64.256,66.153,68.072,68.245,68.741,67.795,67.315,67.245,66.448,69.112,71.787,74.366,76.337,77.618,77.090,76.925,78.384,80.462,82.765,85.033,83.608,81.813,81.467,80.708,80.631,79.133,77.396,75.491,74.267,72.882,71.286,70.737,67.425,67.530,67.157,67.215,66.268,66.053,54.905,54.459,51.159,44.725,40.184,44.094,46.904,47.141,45.052,42.758,41.388,41.154,40.019,39.928,38.598,36.584,32.566,30.140,27.713,25.380,23.823,21.376,18.696,16.304,14.203,11.807,7.551,4.215,3.346,3.010,2.849,2.485,1.744,1.221,803,553,314,204,125,55,53,27,10,6)
> 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 
-67.002682 -21.294452  -8.607563  -0.006946 708.562713 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) 72.05906   10.76616   6.693 1.13e-09 ***
x           -0.02897    0.09206  -0.315    0.754    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 88.99 on 104 degrees of freedom
Multiple R-squared: 0.0009515,	Adjusted R-squared: -0.008655 
F-statistic: 0.09906 on 1 and 104 DF,  p-value: 0.7536 

> postscript(file="/var/www/html/rcomp/tmp/1hc9f1290683554.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/2hc9f1290683554.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 
-2.242e-14 -8.173e-15 -4.035e-15 -9.890e-16  4.739e-13 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  7.206e+01  5.687e-15  1.267e+16   <2e-16 ***
x           -2.897e-02  4.863e-17 -5.958e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4.701e-14 on 104 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 3.549e+29 on 1 and 104 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3al801290683554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
       Min         1Q     Median         3Q        Max 
-67.002682 -21.294452  -8.607563  -0.006946 708.562713 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)
(Intercept) 2.766e-15  1.077e+01 2.57e-16        1
x           7.351e-18  9.206e-02 7.98e-17        1

Residual standard error: 88.99 on 104 degrees of freedom
Multiple R-squared: 1.252e-33,	Adjusted R-squared: -0.009615 
F-statistic: 1.302e-31 on 1 and 104 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/43upl1290683554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
      Min        1Q    Median        3Q       Max 
-21.24601  -0.01752   0.21940   0.82616   1.98488 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 7.004e+01  2.667e-01    262.6   <2e-16 ***
m$residuals 8.625e-18  3.026e-03 2.85e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 2.746 on 104 degrees of freedom
Multiple R-squared: 4.377e-30,	Adjusted R-squared: -0.009615 
F-statistic: 4.552e-28 on 1 and 104 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/5d37o1290683554.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 
-39.4626 -10.6987  -4.6705  -0.3830 744.0874 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  0.28698    7.28101   0.039    0.969    
Residuals    0.55147    0.08227   6.703 1.11e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 74.61 on 103 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.3037,	Adjusted R-squared: 0.297 
F-statistic: 44.93 on 1 and 103 DF,  p-value: 1.115e-09 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6d37o1290683554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7odor1290683554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8odor1290683554.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9h45c1290683554.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/10dell1290683554.tab") 
> 
> try(system("convert tmp/1hc9f1290683554.ps tmp/1hc9f1290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hc9f1290683554.ps tmp/2hc9f1290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/3al801290683554.ps tmp/3al801290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/43upl1290683554.ps tmp/43upl1290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/5d37o1290683554.ps tmp/5d37o1290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/6d37o1290683554.ps tmp/6d37o1290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/7odor1290683554.ps tmp/7odor1290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/8odor1290683554.ps tmp/8odor1290683554.png",intern=TRUE))
character(0)
> try(system("convert tmp/9h45c1290683554.ps tmp/9h45c1290683554.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.803   1.363   4.944