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(2756.76,2849.27,2921.44,2981.85,3080.58,3106.22,3119.31,3061.26,3097.31,3161.69,3257.16,3277.01,3295.32,3363.99,3494.17,3667.03,3813.06,3917.96,3895.51,3801.06,3570.12,3701.61,3862.27,3970.10,4138.52,4199.75,4290.89,4443.91,4502.64,4356.98,4591.27,4696.96,4621.40,4562.84,4202.52,4296.49,4435.23,4105.18,4116.68,3844.49,3720.98,3674.40,3857.62,3801.06,3504.37,3032.60,3047.03,2962.34,2197.82,2014.45,1862.83,1905.41,1810.99,1670.07,1864.44,2052.02,2029.60,2070.83,2293.41)
> x <- c(3016.70,3052.40,3099.60,3103.30,3119.80,3093.70,3164.90,3311.50,3410.60,3392.60,3338.20,3285.10,3294.80,3611.20,3611.30,3521.00,3519.30,3438.30,3534.90,3705.80,3807.60,3663.00,3604.50,3563.80,3511.40,3546.50,3525.40,3529.90,3591.60,3668.30,3728.80,3853.60,3897.70,3640.70,3495.50,3495.10,3268.00,3479.10,3417.80,3521.30,3487.10,3529.90,3544.30,3710.80,3641.90,3447.10,3386.80,3438.50,3364.30,3462.70,3291.90,3550.00,3611.00,3708.60,3771.10,4042.70,3988.40,3851.20,3876.70)
> 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 
-1753.7  -364.6    93.2   649.2  1245.8 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept) 2724.0442  1711.2043   1.592    0.117
x              0.1887     0.4864   0.388    0.700

Residual standard error: 854 on 57 degrees of freedom
Multiple R-squared: 0.002633,	Adjusted R-squared: -0.01486 
F-statistic: 0.1505 on 1 and 57 DF,  p-value: 0.6995 

> postscript(file="/var/www/html/rcomp/tmp/1pzv01258154493.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/2ijlf1258154493.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 
-3.534e-12 -6.861e-14  4.684e-14  2.001e-13  4.986e-13 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 2.724e+03  1.040e-12 2.620e+15   <2e-16 ***
x           1.887e-01  2.956e-16 6.383e+14   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 5.19e-13 on 57 degrees of freedom
Multiple R-squared:     1,	Adjusted R-squared:     1 
F-statistic: 4.075e+29 on 1 and 57 DF,  p-value: < 2.2e-16 

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/360fl1258154493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-1753.7  -364.6    93.2   649.2  1245.8 

Coefficients:
              Estimate Std. Error   t value Pr(>|t|)
(Intercept) -2.960e-14  1.711e+03 -1.73e-17        1
x            0.000e+00  4.864e-01         0        1

Residual standard error: 854 on 57 degrees of freedom
Multiple R-squared: 2.018e-34,	Adjusted R-squared: -0.01754 
F-statistic: 1.15e-32 on 1 and 57 DF,  p-value: 1 

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4n6641258154493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-93.231 -22.856   1.973  24.614 100.347 

Coefficients:
             Estimate Std. Error  t value Pr(>|t|)    
(Intercept) 3.386e+03  5.712e+00    592.8   <2e-16 ***
m$residuals 9.037e-17  6.806e-03 1.33e-14        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 43.88 on 57 degrees of freedom
Multiple R-squared: 1.884e-30,	Adjusted R-squared: -0.01754 
F-statistic: 1.074e-28 on 1 and 57 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/5ckig1258154493.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 
-744.17  -84.64   39.10  126.61  243.14 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) -10.58000   24.22254  -0.437    0.664    
Residuals     0.98970    0.02909  34.024   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 184.4 on 56 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared: 0.9539,	Adjusted R-squared: 0.953 
F-statistic:  1158 on 1 and 56 DF,  p-value: < 2.2e-16 

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/6uent1258154493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/7l7mc1258154493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/8xbr91258154493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/9u9t51258154493.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/10j8wp1258154493.tab") 
> 
> system("convert tmp/1pzv01258154493.ps tmp/1pzv01258154493.png")
> system("convert tmp/2ijlf1258154493.ps tmp/2ijlf1258154493.png")
> system("convert tmp/360fl1258154493.ps tmp/360fl1258154493.png")
> system("convert tmp/4n6641258154493.ps tmp/4n6641258154493.png")
> system("convert tmp/5ckig1258154493.ps tmp/5ckig1258154493.png")
> system("convert tmp/6uent1258154493.ps tmp/6uent1258154493.png")
> system("convert tmp/7l7mc1258154493.ps tmp/7l7mc1258154493.png")
> system("convert tmp/8xbr91258154493.ps tmp/8xbr91258154493.png")
> system("convert tmp/9u9t51258154493.ps tmp/9u9t51258154493.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.824   1.361   2.281