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(45943,59385,7176,63907,112746,218511,51741,60400,63412,125468,50224,81908,35821,71437,59999,64114,49519,14903,56100,11805,33983,77726,47624,44572,61932,47968,64711,59855,130532,71572,55974,73726,44795,24608,65081,0,45624,60122,31241,73314,65398,41061,30085,44881,35236,24791,24886,87233,55304,42244,33820,37861,77191,76157,81220,46992,58593,22923,48977,17919,28651,27666,22528,33493,41603,44299,49670,58803,31404,12185,83343,25915,29352,35557,23272,17647,51193,35126,15563,21057,22050,66490,27190,48592,21764,47480,74948,17111,28728,45984,45664,51855,46737,46743,14189,102297,58066,19349,60378,47671,12992,17528,34532,17934,22361,20460,47949,16231,0,23392,20284,44393,35245,34131,3058,0,71090,24715,50785,33277,43051,61450,24215,25685,32306,15802,27437,34800,47050,11747,6046,41621,6836,11056,510,6669,0,28068,8916,7131,4194,14160,11970,26174)
> x <- c(9492,8767,1423,15387,11936,22386,7703,7694,14513,12552,10893,14584,5469,8334,8651,13657,22452,6023,10602,12476,783,16597,5506,5852,6630,4065,12579,10432,50116,8628,3482,7195,11938,15129,5050,0,7537,8665,3710,11128,7980,6851,15966,22214,7713,6154,2928,10805,17412,9243,6656,3585,11016,14667,11708,7619,11853,9540,10081,2574,3772,3886,8984,5956,10878,9852,13736,8033,9776,1536,6948,5846,7318,4898,1358,0,9580,17612,2941,6924,6387,3690,7153,8765,5761,8809,10686,8055,8352,6030,14070,17349,5645,4120,13983,3853,19150,3895,4408,7498,2325,11429,17265,6265,3087,3979,8931,3721,0,6185,14254,7500,5890,0,0,0,10411,28040,103,14377,2781,8759,2229,2423,13656,2790,10255,4845,5264,0,0,0,0,0,0,0,0,7711,797,0,0,4010,5959,2338)
> 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 
-65241 -15211  -2737  11941 142167 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 2.245e+04  3.221e+03   6.969 1.10e-10 ***
x           2.408e+00  3.142e-01   7.663 2.59e-12 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 24510 on 142 degrees of freedom
Multiple R-squared: 0.2925,	Adjusted R-squared: 0.2876 
F-statistic: 58.72 on 1 and 142 DF,  p-value: 2.593e-12 

> postscript(file="/var/wessaorg/rcomp/tmp/1pblf1321549500.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/24m9d1321549500.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 
-2.327e-11 -1.910e-12  3.292e-13  2.271e-12  8.475e-12 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 2.245e+04  4.967e-13 4.519e+16   <2e-16 ***
x           2.408e+00  4.845e-17 4.969e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 3.779e-12 on 142 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 2.469e+33 on 1 and 142 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3gf2p1321549500.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
   Min     1Q Median     3Q    Max 
-65241 -15211  -2737  11941 142167 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  5.440e-14  3.221e+03       0        1
x           -1.091e-17  3.142e-01       0        1

Residual standard error: 24510 on 142 degrees of freedom
Multiple R-squared: 2.422e-36,	Adjusted R-squared: -0.007042 
F-statistic: 3.44e-34 on 1 and 142 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4lxwh1321549500.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
   Min     1Q Median     3Q    Max 
-19088 -10136  -1617   6970 101571 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  4.154e+04  1.313e+03   31.63   <2e-16 ***
m$residuals -5.501e-17  5.396e-02    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 15760 on 142 degrees of freedom
Multiple R-squared: 1.216e-31,	Adjusted R-squared: -0.007042 
F-statistic: 1.727e-29 on 1 and 142 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/5i1ft1321549500.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 
-68008 -15715  -2651  12006 134935 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)   -6.05660 2042.41602  -0.003    0.998
Residuals      0.11758    0.08363   1.406    0.162

Residual standard error: 24420 on 141 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.01382,	Adjusted R-squared: 0.00683 
F-statistic: 1.977 on 1 and 141 DF,  p-value: 0.162 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6yg6p1321549500.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/75h9n1321549500.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/88n2x1321549500.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9ync31321549500.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/109mhq1321549500.tab") 
> 
> try(system("convert tmp/1pblf1321549500.ps tmp/1pblf1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/24m9d1321549500.ps tmp/24m9d1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gf2p1321549500.ps tmp/3gf2p1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/4lxwh1321549500.ps tmp/4lxwh1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/5i1ft1321549500.ps tmp/5i1ft1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/6yg6p1321549500.ps tmp/6yg6p1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/75h9n1321549500.ps tmp/75h9n1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/88n2x1321549500.ps tmp/88n2x1321549500.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ync31321549500.ps tmp/9ync31321549500.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.784   0.457   3.261