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(1235,1080,845,1522,1047,1979,1822,1253,1297,946,1713,1024,1147,1092,1152,1336,2131,1550,1884,2041,845,1483,1055,1545,729,1792,1175,1593,785,744,1356,1262,1250,1020,840,1515,1045,1972,1820,1248,1290,944,1713,1022,1143,1089,1149,1327,2128,1143,1880,2034,844,1879,1050,1541,724,1782,1170,1586,749,740,1352)
> x <- c(127,115,127,150,156,182,156,132,137,113,137,117,137,153,117,126,170,182,162,184,143,159,108,175,108,179,111,187,111,115,194,168,125,114,126,149,155,181,155,130,136,112,135,114,136,152,116,125,169,181,160,183,142,158,107,174,107,178,110,186,110,114,193)
> 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 
-567.61 -217.61   45.25  196.68  542.53 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -176.977    192.968  -0.917    0.363    
x             10.429      1.317   7.918 6.09e-11 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 283.1 on 61 degrees of freedom
Multiple R-squared: 0.5068,	Adjusted R-squared: 0.4988 
F-statistic: 62.69 on 1 and 61 DF,  p-value: 6.092e-11 

> postscript(file="/var/wessaorg/rcomp/tmp/1zvo21321792131.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/2g7e11321792131.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 
-4.360e-13 -3.836e-14 -1.301e-14  4.193e-14  4.147e-13 

Coefficients:
              Estimate Std. Error    t value Pr(>|t|)    
(Intercept) -1.770e+02  7.302e-14 -2.424e+15   <2e-16 ***
x            1.043e+01  4.984e-16  2.092e+16   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 1.071e-13 on 61 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 4.379e+32 on 1 and 61 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3ltns1321792131.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-567.61 -217.61   45.25  196.68  542.53 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -5.001e-15  1.930e+02       0        1
x           -1.198e-17  1.317e+00       0        1

Residual standard error: 283.1 on 61 degrees of freedom
Multiple R-squared: 6.225e-35,	Adjusted R-squared: -0.01639 
F-statistic: 3.797e-33 on 1 and 61 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4y7hd1321792131.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-385.70 -286.62  -72.84  255.67  521.60 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  1.325e+03  3.616e+01   36.63   <2e-16 ***
m$residuals -5.377e-17  1.298e-01    0.00        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 287 on 61 degrees of freedom
Multiple R-squared: 3.704e-31,	Adjusted R-squared: -0.01639 
F-statistic: 2.26e-29 on 1 and 61 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/54lvu1321792131.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 
-528.89 -225.17   47.23  206.17  557.38 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.86735   36.15215  -0.024    0.981
Residuals   -0.06979    0.13195  -0.529    0.599

Residual standard error: 284.5 on 60 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.00464,	Adjusted R-squared: -0.01195 
F-statistic: 0.2797 on 1 and 60 DF,  p-value: 0.5988 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6ixj51321792131.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/78web1321792131.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8aoi91321792131.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9k6c01321792131.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/10dq2z1321792131.tab") 
> 
> try(system("convert tmp/1zvo21321792131.ps tmp/1zvo21321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/2g7e11321792131.ps tmp/2g7e11321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ltns1321792131.ps tmp/3ltns1321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/4y7hd1321792131.ps tmp/4y7hd1321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/54lvu1321792131.ps tmp/54lvu1321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ixj51321792131.ps tmp/6ixj51321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/78web1321792131.ps tmp/78web1321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/8aoi91321792131.ps tmp/8aoi91321792131.png",intern=TRUE))
character(0)
> try(system("convert tmp/9k6c01321792131.ps tmp/9k6c01321792131.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.375   0.577   3.010