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(1687,1508,1507,1385,1632,1511,1559,1630,1579,1653,2152,2148,1752,1765,1717,1558,1575,1520,1805,1800,1719,2008,2242,2478,2030,1655,1693,1623,1805,1746,1795,1926,1619,1992,2233,2192,2080,1768,1835,1569,1976,1853,1965,1689,1778,1976,2397,2654,2097,1963,1677,1941,2003,1813,2012,1912,2084,2080,2118,2150,1608,1503,1548,1382,1731,1798,1779,1887,2004,2077,2092,2051,1577,1356,1652,1382,1519,1421,1442,1543,1656,1561,1905,2199,1473,1655,1407,1395,1530,1309,1526,1327,1627,1748,1958,2274,1648,1401,1411,1403,1394,1520,1528,1643,1515,1685,2000,2215,1956,1462,1563,1459,1446,1622,1657,1638,1643,1683,2050,2262,1813,1445,1762,1461,1556,1431,1427,1554,1645,1653,2016,2207,1665,1361,1506,1360,1453,1522,1460,1552,1548,1827,1737,1941,1474,1458,1542,1404,1522,1385,1641,1510,1681,1938,1868,1726,1456,1445,1456,1365,1487,1558,1488,1684,1594,1850,1998,2079,1494,1057,1218,1168,1236,1076,1174,1139,1427,1487,1483,1513,1357,1165,1282,1110,1297,1185,1222,1284,1444,1575,1737,1763)
> x <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1)
> 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 
-408.75 -198.00  -63.75  188.26  936.25 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1717.75      20.00  85.886  < 2e-16 ***
x            -396.06      57.79  -6.854 9.76e-11 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 260 on 190 degrees of freedom
Multiple R-squared: 0.1982,	Adjusted R-squared: 0.194 
F-statistic: 46.97 on 1 and 190 DF,  p-value: 9.763e-11 

> postscript(file="/var/www/html/rcomp/tmp/1z2nr1290717542.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/2rtmu1290717542.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 
-6.529e-11  3.931e-13  3.931e-13  3.931e-13  3.931e-13 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept)  1.718e+03  3.654e-13  4.701e+15   <2e-16 ***
x           -3.961e+02  1.056e-12 -3.751e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 4.751e-12 on 190 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 1.407e+29 on 1 and 190 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3233f1290717542.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-408.75 -198.00  -63.75  188.26  936.25 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -6.128e-15  2.000e+01 -3.06e-16        1
x            1.263e-14  5.779e+01  2.19e-16        1

Residual standard error: 260 on 190 degrees of freedom
Multiple R-squared: 4.24e-34,	Adjusted R-squared: -0.005263 
F-statistic: 8.056e-32 on 1 and 190 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4233f1290717542.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-348.61   47.44   47.44   47.44   47.44 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 1.670e+03  9.330e+00    179.0   <2e-16 ***
m$residuals 1.348e-16  3.607e-02 3.74e-15        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 129.3 on 190 degrees of freedom
Multiple R-squared: 5.903e-28,	Adjusted R-squared: -0.005263 
F-statistic: 1.122e-25 on 1 and 190 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/5vuk01290717542.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 
-557.916 -125.632    2.128  139.569  510.430 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.65656   14.45663   0.115    0.909    
Residuals    0.64729    0.05618  11.523   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 199.8 on 189 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.4126,	Adjusted R-squared: 0.4095 
F-statistic: 132.8 on 1 and 189 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/663131290717542.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/763131290717542.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8guj51290717542.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9guj51290717542.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/105ejr1290717543.tab") 
> 
> try(system("convert tmp/1z2nr1290717542.ps tmp/1z2nr1290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rtmu1290717542.ps tmp/2rtmu1290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/3233f1290717542.ps tmp/3233f1290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/4233f1290717542.ps tmp/4233f1290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vuk01290717542.ps tmp/5vuk01290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/663131290717542.ps tmp/663131290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/763131290717542.ps tmp/763131290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/8guj51290717542.ps tmp/8guj51290717542.png",intern=TRUE))
character(0)
> try(system("convert tmp/9guj51290717542.ps tmp/9guj51290717542.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.923   1.471   5.680