R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> y <- c(149
+ ,139
+ ,148
+ ,158
+ ,128
+ ,224
+ ,159
+ ,105
+ ,159
+ ,167
+ ,165
+ ,159
+ ,119
+ ,176
+ ,54
+ ,91
+ ,163
+ ,124
+ ,137
+ ,121
+ ,153
+ ,148
+ ,221
+ ,188
+ ,149
+ ,244
+ ,148
+ ,92
+ ,150
+ ,153
+ ,94
+ ,156
+ ,132
+ ,161
+ ,105
+ ,97
+ ,151
+ ,131
+ ,166
+ ,157
+ ,111
+ ,145
+ ,162
+ ,163
+ ,59
+ ,187
+ ,109
+ ,90
+ ,105
+ ,83
+ ,116
+ ,42
+ ,148
+ ,155
+ ,125
+ ,116
+ ,128
+ ,138
+ ,49
+ ,96
+ ,164
+ ,162
+ ,99
+ ,202
+ ,186
+ ,66
+ ,183
+ ,214
+ ,188
+ ,104
+ ,177
+ ,126
+ ,76
+ ,99
+ ,139
+ ,162
+ ,108
+ ,159
+ ,74
+ ,110
+ ,96
+ ,116
+ ,87
+ ,97
+ ,127
+ ,106
+ ,80
+ ,74
+ ,91
+ ,133
+ ,74
+ ,114
+ ,140
+ ,95
+ ,98
+ ,121
+ ,126
+ ,98
+ ,95
+ ,110
+ ,70
+ ,102
+ ,86
+ ,130
+ ,96
+ ,102
+ ,100
+ ,94
+ ,52
+ ,98
+ ,118
+ ,99
+ ,48
+ ,50
+ ,150
+ ,154
+ ,109
+ ,68
+ ,194
+ ,158
+ ,159
+ ,67
+ ,147
+ ,39
+ ,100
+ ,111
+ ,138
+ ,101
+ ,131
+ ,101
+ ,114
+ ,165
+ ,114
+ ,111
+ ,75
+ ,82
+ ,121
+ ,32
+ ,150
+ ,117
+ ,71
+ ,165
+ ,154
+ ,126
+ ,149
+ ,145
+ ,120
+ ,109
+ ,132
+ ,172
+ ,169
+ ,114
+ ,156
+ ,172
+ ,68
+ ,89
+ ,167
+ ,113
+ ,115
+ ,78
+ ,118
+ ,87
+ ,173
+ ,2
+ ,162
+ ,49
+ ,122
+ ,96
+ ,100
+ ,82
+ ,100
+ ,115
+ ,141
+ ,165
+ ,165
+ ,110
+ ,118
+ ,158
+ ,146
+ ,49
+ ,90
+ ,121
+ ,155
+ ,104
+ ,147
+ ,110
+ ,108
+ ,113
+ ,115
+ ,61
+ ,60
+ ,109
+ ,68
+ ,111
+ ,77
+ ,73
+ ,151
+ ,89
+ ,78
+ ,110
+ ,220
+ ,65
+ ,141
+ ,117
+ ,122
+ ,63
+ ,44
+ ,52
+ ,131
+ ,101
+ ,42
+ ,152
+ ,107
+ ,77
+ ,154
+ ,103
+ ,96
+ ,175
+ ,57
+ ,112
+ ,143
+ ,49
+ ,110
+ ,131
+ ,167
+ ,56
+ ,137
+ ,86
+ ,121
+ ,149
+ ,168
+ ,140
+ ,88
+ ,168
+ ,94
+ ,51
+ ,48
+ ,145
+ ,66
+ ,85
+ ,109
+ ,63
+ ,102
+ ,162
+ ,86
+ ,114
+ ,164
+ ,119
+ ,126
+ ,132
+ ,142
+ ,83
+ ,94
+ ,81
+ ,166
+ ,110
+ ,64
+ ,93
+ ,104
+ ,105
+ ,49
+ ,88
+ ,95
+ ,102
+ ,99
+ ,63
+ ,76
+ ,109
+ ,117
+ ,57
+ ,120
+ ,73
+ ,91
+ ,108
+ ,105
+ ,117
+ ,119
+ ,31)
> x <- c(68,39,32,62,33,52,62,77,76,41,48,63,30,78,19,31,66,35,42,45,21,25,44,69,54,74,80,42,61,41,46,39,34,51,42,31,39,20,49,53,31,39,54,49,34,46,55,42,50,13,37,25,30,28,45,35,28,41,6,45,73,17,40,64,37,25,65,100,28,35,56,29,43,59,50,59,27,61,28,51,35,29,48,25,44,64,32,20,28,34,31,26,58,23,21,21,33,16,20,37,35,33,27,41,40,35,28,32,22,44,27,17,12,45,37,37,108,10,68,72,143,9,55,17,37,27,37,58,66,21,19,78,35,48,27,43,30,25,69,72,23,13,61,43,51,67,36,44,45,34,36,72,39,43,25,56,80,40,73,34,72,42,61,23,74,16,66,9,41,57,48,51,53,29,29,55,54,43,51,20,79,39,61,55,30,55,22,37,2,38,27,56,25,39,33,43,57,43,23,44,54,28,36,39,16,23,40,24,78,57,37,27,61,27,69,34,44,34,39,51,34,31,13,12,51,24,19,30,81,42,22,85,27,25,22,19,14,45,45,28,51,41,31,74,19,51,73,24,61,23,14,54,51,62,36,59,24,26,54,39,16,36,31,31,42,39,25,31,38,31,17,22,55,62,51,30,49,16)
> par1 = '0'
> ylab = 'y'
> xlab = 'x'
> par1 <- '0'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), Linear Regression Graphical Model Validation (v1.0.7) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_linear_regression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> 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 
-97.211 -26.853  -3.505  23.500 102.201 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  77.7575     5.1304  15.156  < 2e-16 ***
x             0.9327     0.1125   8.289 5.03e-15 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 35.71 on 276 degrees of freedom
Multiple R-squared:  0.1993,	Adjusted R-squared:  0.1964 
F-statistic: 68.71 on 1 and 276 DF,  p-value: 5.026e-15

> postscript(file="/var/wessaorg/rcomp/tmp/1gg6a1418459922.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/2gvwv1418459922.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 
-4.690e-14 -1.165e-14 -5.660e-15 -4.700e-16  1.655e-12 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 7.776e+01  1.470e-14 5.291e+15   <2e-16 ***
x           9.327e-01  3.223e-16 2.894e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.023e-13 on 276 degrees of freedom
Multiple R-squared:      1,	Adjusted R-squared:      1 
F-statistic: 8.373e+30 on 1 and 276 DF,  p-value: < 2.2e-16

> z2 <- as.data.frame(cbind(x,m$fitted.values))
> names(z2) <- list('x','Fitted')
> plot(z2,main='Scatterplot, lowess, and regression line')
> lines(lowess(z2),col='red')
> abline(m2)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3spz51418459922.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m3 <- lm(m$residuals ~ x)
> summary(m3)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-97.211 -26.853  -3.505  23.500 102.201 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.029e-14  5.130e+00       0        1
x            1.455e-16  1.125e-01       0        1

Residual standard error: 35.71 on 276 degrees of freedom
Multiple R-squared:  4.609e-32,	Adjusted R-squared:  -0.003623 
F-statistic: 1.272e-29 on 1 and 276 DF,  p-value: 1

> z3 <- as.data.frame(cbind(x,m$residuals))
> names(z3) <- list('x','Residuals')
> plot(z3,main='Scatterplot, lowess, and regression line')
> lines(lowess(z3),col='red')
> abline(m3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/43co41418459922.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> m4 <- lm(m$fitted.values ~ m$residuals)
> summary(m4)

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

Residuals:
    Min      1Q  Median      3Q     Max 
-36.780 -12.528  -2.268  11.490  94.738 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.164e+02  1.069e+00   108.9   <2e-16 ***
m$residuals 5.614e-17  3.003e-02     0.0        1    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 17.82 on 276 degrees of freedom
Multiple R-squared:  2.642e-29,	Adjusted R-squared:  -0.003623 
F-statistic: 7.293e-27 on 1 and 276 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/5rr9w1418459922.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 
-100.69  -26.12   -2.09   23.93   97.93 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.04873    2.14021  -0.023    0.982
Residuals    0.09213    0.06037   1.526    0.128

Residual standard error: 35.62 on 275 degrees of freedom
  (2 observations deleted due to missingness)
Multiple R-squared:  0.008397,	Adjusted R-squared:  0.004792 
F-statistic: 2.329 on 1 and 275 DF,  p-value: 0.1281

> abline(m5)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6wyf81418459922.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> hist(m$residuals,main='Residual Histogram',xlab='Residuals')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7r8ga1418459922.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if (par1 > 0)
+ {
+ densityplot(~m$residuals,col='black',main=paste('Density Plot   bw = ',par1),bw=par1)
+ } else {
+ densityplot(~m$residuals,col='black',main='Density Plot')
+ }
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/8mla51418459922.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> acf(m$residuals,main='Residual Autocorrelation Function')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/9mhdu1418459922.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/10iur41418459922.tab") 
> 
> try(system("convert tmp/1gg6a1418459922.ps tmp/1gg6a1418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gvwv1418459922.ps tmp/2gvwv1418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/3spz51418459922.ps tmp/3spz51418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/43co41418459922.ps tmp/43co41418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rr9w1418459922.ps tmp/5rr9w1418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/6wyf81418459922.ps tmp/6wyf81418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/7r8ga1418459922.ps tmp/7r8ga1418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/8mla51418459922.ps tmp/8mla51418459922.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mhdu1418459922.ps tmp/9mhdu1418459922.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.218   0.489   3.757