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(2845,2234,603,6113,4648,4632,2404,2159,5660,3571,5285,5774,2597,2264,1233,2292,7207,1,4131,1824,495,5345,594,881,2398,1818,3241,4053,4373,3887,1,2662,3044,31,1658,0,2233,3223,783,3011,2196,2591,1647,1890,1353,1883,1095,2079,4174,2808,1783,1780,1917,2865,2290,2489,2584,2098,3715,76,2356,967,1091,1588,1881,2636,5431,1833,3009,516,1574,416,1377,2019,437,0,2881,1997,1706,1651,40,1730,1825,3202,302,2316,4208,1584,2204,2391,2571,2458,1191,471,2280,1978,2540,786,2282,1806,593,1235,2242,2395,953,460,3009,983,0,2178,349,1830,1992,0,0,0,4975,1768,52,2245,4,1335,624,84,358,1186,3070,1748,1815,0,0,0,0,0,0,0,0,1769,361,0,0,1239,1993,753)
> 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 
-3622.5  -738.4   -88.0   648.5  3217.4 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 738.42329  153.34266   4.816 3.72e-06 ***
x             0.14480    0.01496   9.681  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1167 on 142 degrees of freedom
Multiple R-squared: 0.3976,	Adjusted R-squared: 0.3934 
F-statistic: 93.73 on 1 and 142 DF,  p-value: < 2.2e-16 

> postscript(file="/var/wessaorg/rcomp/tmp/1grfh1321559878.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/2luu71321559878.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 
-4.683e-13 -7.363e-14  6.040e-15  5.613e-14  9.809e-13 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 7.384e+02  2.092e-14 3.530e+16   <2e-16 ***
x           1.448e-01  2.040e-18 7.097e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.592e-13 on 142 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 5.037e+33 on 1 and 142 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3j6lf1321559878.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-3622.5  -738.4   -88.0   648.5  3217.4 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept)  2.026e-14  1.533e+02       0        1
x           -9.896e-19  1.496e-02       0        1

Residual standard error: 1167 on 142 degrees of freedom
Multiple R-squared: 2.922e-34,	Adjusted R-squared: -0.007042 
F-statistic: 4.149e-32 on 1 and 142 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4pgac1321559878.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-1148.0  -609.6   -97.3   419.2  6109.0 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.886e+03  7.899e+01   23.88   <2e-16 ***
m$residuals 2.198e-17  6.818e-02    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 947.9 on 142 degrees of freedom
Multiple R-squared: 4.052e-32,	Adjusted R-squared: -0.007042 
F-statistic: 5.754e-30 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/52nqc1321559878.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 
-3559.4  -749.3  -104.7   629.0  3208.8 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) -5.04661   97.72056  -0.052    0.959
Residuals   -0.03217    0.08408  -0.383    0.703

Residual standard error: 1169 on 141 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.001037,	Adjusted R-squared: -0.006048 
F-statistic: 0.1464 on 1 and 141 DF,  p-value: 0.7026 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/605yw1321559878.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7c9un1321559878.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8ocf51321559878.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/94vmq1321559878.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/10pgx91321559878.tab") 
> 
> try(system("convert tmp/1grfh1321559878.ps tmp/1grfh1321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/2luu71321559878.ps tmp/2luu71321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/3j6lf1321559878.ps tmp/3j6lf1321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/4pgac1321559878.ps tmp/4pgac1321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/52nqc1321559878.ps tmp/52nqc1321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/605yw1321559878.ps tmp/605yw1321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/7c9un1321559878.ps tmp/7c9un1321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ocf51321559878.ps tmp/8ocf51321559878.png",intern=TRUE))
character(0)
> try(system("convert tmp/94vmq1321559878.ps tmp/94vmq1321559878.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.472   0.449   2.955